With over 2.7 billion smartphone users and 1.35 billion tablet users globally, there are 2.8 million apps on the Google Play Store and over 2.2 million apps on the Apple App Store. In fact, there were over 205 billion app downloads in 2019 alone.

That’s staggering!

Sure there’s a massive opportunity to empower users, strengthen your online presence, generate top-line revenues, and counter competition — but, that’s easier said than done.

One fool-proof way to consistently power user engagement, conversions, and retention at scale is by integrating a strong personalization strategy into your mobile (and omnichannel) marketing machinery, backed by strong UI/UX.

And, personalization — today — has gone above and beyond the obvious. Addressing your users by their first names over a push notification or sending them a discount coupon on their birthdays over an email campaign is great.

But, it’s not enough! And, especially so in the current COVID-19 environment where hyper-competition for users’ screen-share, mind-share, and wallet-share has only heightened.

Your users expect and demand an end-to-end, tailor-made customer experience, right from first-time app launch. This assumes even greater significance across industries such as e-commerce, OTT, and news and media.

Here’s how you can now deliver highly differentiated CX at scale on and through your mobile app:

1. Build a solid foundation of and on user data:

Effective personalization is dependent on you gathering the right user data across channels and platforms. Gathering the right demographic, geolocation, and device-type data-points is important. Start capturing these basic data-points at the registration or login stage of your user onboarding flow.

But, you also need to capture your users’ in-app behaviors, actions, inactions, responses and interactions to multi-channel marketing campaigns. This will help you create and constantly enrich a unified view of every user, in real-time.

For instance, if you’re an e-commerce app, you need to log actions and details such as products searched, product categories browsed, products added to cart or wishlist, products purchased, payment mode chosen, and most common paths towards conversion.

If you have a physical store, you also need to ensure your transactional data is funneling back into your data backend so as to personalize subsequent shopping experiences across both your website and/or app.

Simultaneously, you need to track relevant metrics attached to these actions to gather granular insights — recency and frequency of app launches and purchases, average time spent per screen, ratio of products added to cart and finally purchased, actual conversion rates, etc.

Analyzing these diverse data-points will help you gain actionable insights and develop relevant user segments.

AI can help you dive deeper. Now slice and dice behavioral data to arrive at a segment of one, with AI doing all the heavy-lifting for you! Cutting-edge collaborative and content-filtering algorithms make it possible to ingest large amounts of user data-points and behavioral footprints.

Once you have your user data and analytics backbone in place, you can focus on adding muscle to your personalization strategy.

2. Personalize the app home screen on the first-time launch:

Modern marketing has driven home the fact that one size doesn’t fit all. Depending upon your app category and the quality (and quantity) of demographic data-points that you’re able to gather during the first-time onboarding flow — you can immediately start delivering a personalized user experience on your app home screen.

For instance: If you are an OTT music streaming app; data-points like name, age, gender, preferred genres and languages, favorite artists, etc. can be used to curate a first-degree personalized list of content recommendations on your app home screen instantly.

You need to strike the right balance between deploying an onboarding flow that educates new users on functionality, key features, etc. and capturing relevant demographic data-points (without being explicitly intrusive) to start delivering 1:1 user experiences ASAP.

Notice how Hungama Music, one of India’s leading home-grown music streaming apps, does this during the user onboarding process to quickly begin personalizing content recommendations when the home screen launches for the first time.

You can subsequently highlight the most relevant recommendations on the app home screen on future app launches. This can increase your CTRs by 90–120% while uplifting content consumption by 5–7%!

3. Tailor-make the app navigation experience:

Apart from your users’ search, browsing, click behavior and consumption history, you can personalize how your users navigate across your mobile app.

Other parameters such as gender, buyer personas, geolocation, time of day/timezone, seasons/weather, etc. can be harnessed to personalize the banner images, graphics, CTAs, trending products and offers, etc.

Also, leverage insights from your users’ most common paths towards conversion to further optimize their navigation journey. The more individualized the navigation journey, greater the probability of your users finding exactly what they want, faster!

Check out how AJIO, a leading e-commerce clothing retailer offers a gender-based app navigation experience for both men and women.

4. Personalize the search experience:

Any search made by a user on your app is a solid signal of intent. Intent to purchase a product. Intent to book a ticket. Intent to consume content. And, you need to value these search inputs.

Every search action undertaken by specific users tells you about their instant wants, needs, and preferences. And, your objective must be to direct your users to exactly what they want faster.

With the assistance of our AI, you can now instantly populate product or content recommendations based on the partial or full search terms inputted in the search tab. This would also take into account historical searches made.

These recommendations continue to get more accurate with each subsequent search action that a user takes, helping you to significantly reduce the path from product discovery to purchase.

For instance: As an e-commerce platform that specializes in the online retail of cosmetics, you can start giving the most relevant product recommendations for lipsticks when a user is searching for a particular brand of lipsticks.

Here’s how Amazon leverages search personalization to show me sub-product categories that are most relevant to me.

5. Showcase real-time AI-led predictive recommendations:

Falling user attention spans and quick access to alternate apps in the same category can fuel switching behavior. This is why you need to respect the time an individual user potentially invests when he/she launches your app. Near-instant product discovery and top-of-sight visibility become critical to conversions or consumption.

AI now enables you to show the most relevant product or content recommendations across your Home Screen, Product Display Screen, and Product Listing Screen.

These live recommendations can be optimized for mobile display and click, ensuring that you maximize the use of screen-space on every scroll.

Moreover, these recommendations get more refined with each shopping session that an individual user engages in.

A robust AI engine, today, must account for clickstream data and customer eyeball data.

This implies that negative signals for any product or content recommendations that are “seen-and-not clicked” and “not seen-and-not clicked” should feed right back into the AI engine — in real-time.

This helps you improve behavioral predictions by almost 20%.

6. Re-order product or content categories for greater context:

If you have an e-commerce, OTT, or news and media app; you are bound to have hundreds of products or content options within your product catalog or content library.

With the help of AI, you can now re-order these categories in real-time for individual users so the most relevant product or content recommendations show up right at the top.

Remember the Golden Rule?

Near-instant product discovery and top-of-sight visibility become critical to conversions or consumption!

7. Create an in-app personalized storefront or playlist:

Why not go one step further on your UX personalization journey and create a unique mobile boutique — composed of only those products or content recommendations that an individual user is most likely to view, buy, or consume on your app?

Delight your users with a unique online shopping or content consumption experience while increasing CTRs by 120–150%, every time they launch your app.

A dynamic AI engine will feed off neural networks to bolster its real-time, reinforced learning capacity; as it refreshes the list of recommendations every time a user chooses to launch the personalized storefront, watch-list, playlist, or read-list.

Spotify actually goes a step further to create multiple weekly playlists based on preferred genres, favorite artists, and music language.

8. Deploy live contextual recommendations via in-app messages:

You can optimize your in-app personalization strategy by triggering relevant product or content recommendations and appropriate offers at individual users through in-app messages.

These can be triggered when a user lands on certain pre-defined screens or when a user scrolls a finite percentage on certain pre-defined screens.

AI can help trigger these in-app messages only when they truly make sense, without disrupting the ongoing user experience.

For instance: As an e-commerce app that has a health and hygiene product category, if a user has added hand sanitizers to his/her cart, you can trigger a relevant recommendation for facemasks and hand-washes, as a dynamic product bundle.

Such a strategy can also help you increase your average order value through effective cross-sell and upsell opportunities.

9. Personalize your recommendations across other channels:

While personalizing the entire in-app mobile experience is important, what do you do when your user is not in an active session? You can’t leave that to chance.

The essence of personalization lies in delivering a rich and unique 1:1 CX across multiple digital touchpoints. This implies that you need to activate other critical mobile marketing channels such as emails and app push notifications to continue delivering these personalized recommendations.

With AI, you can now trigger laser-focused product recommendations across these channels to maintain top-of-mind recall, bring inactive users back to your app, and potentially nudge them towards a conversion event.

10. Re-target existing users with personalized ads:

Regardless of your best efforts at encouraging your users to make a purchase or spend more time-consuming content on your app, there will be drop-offs and users that straddle dormancy.

That’s the harsh reality of mobile marketing!

With AI, you can now target individual users with the most relevant product or content recommendations through optimized re-targeting ads across Google, Facebook, and Instagram — at the right time.

For instance: As an e-commerce app specializing in fashion apparel, you can re-target existing users with the most relevant t-shirt, shirt, or trouser related recommendations that are most contextual to individual male users.

Depending upon where a user is most likely to see this ad, the AI engine will display a mobile-optimized ad, nudging the user to click and re-launch your app.

Personalization at Scale = Stickier 1:1 Experiences = User Retention

Mobile app personalization is not a set-it-and-forget-it project. While AI will help you deliver relevant recommendation-led 1:1 user experiences; human intelligence also plays an important role.

When AI and human intelligence — in terms of UI/UX — come together, you can continue to optimize experiences for a segment of one!

Also, remember that mobile app personalization is another weapon in your larger omnichannel personalization arsenal. Wowing your users just on one platform is not going to cut it! They expect a consistent and frictionless experience across your website, mobile app, and marketing channels (across devices).

Mobile app personalization: when UI meets AI to elevate CX was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

The ongoing COVID-19 pandemic has come as a “White Swan” event that is likely to wipe out $2.7 trillion from the global economy in lost output.

Set in a quasi-uncertain backdrop, e-commerce brands are coming to grips with evolving consumer behaviour trends, purchase patterns, and situational habits.

Making Sense of the New Normal

According to a recent Nielsen research report, there are six major consumer behavior thresholds pertaining to the COVID-19-necessitated lockdown across countries:

Most of the developed and emerging economies have already gone through the first three levels. Consumer behavior patterns across the next three levels are now beginning to take shape as sustained global stay-at-home periods are likely to get extended.

Levels 4, 5, and 6 also provide online retailers with an opportunity to proactively respond to new demand signals across demographics. By keeping a firm pulse on your digital customers’ new needs, wants, likes, dislikes, and expectations — you can personalize the entire customer experience by delivering value at every stage across individual lifecycles.

To help you effectively combat these unprecedented times, re-imagine growth in a post COVID-19 era, and deliver customer delight at scale with omnichannel personalization — I’ve outlined 8 key action steps:

1. Analyze your customer data to unearth new actionable insights:

Fact: Existing chapters of the marketing playbook — as you know it — may no longer be relevant. And, altogether new chapters are being written into it, on an almost weekly basis.

As an e-commerce brand, what worked for you until February, 2020; is unlikely to shape your future customer and revenue growth engine.

So, double-down on gathering and unifying the right customer data. Build and gain a 360-degree view of individual digital customers based on their demographic, geolocation, behavioral, and device-related data points.

Slice-and-dice this data to gather new actionable insights on evolving consumer behavior trends.

You are more than likely to uncover higher engagement and conversion rates from customer segments that previously scored lowly on RFM parameters; i.e. Recency, Frequency, and Monetary Value of purchase.

For instance: Confined indoors and without access to physical grocery stores or pharmacies; senior citizens have taken to ordering items of need online over websites and apps. This has brought an outlier customer segment into sharp focus during the current COVID-19 crisis.

These new customer segments open up new avenues to increase CLTV and retention in the long-run through an AI-led omnichannel personalization strategy.

But, don’t allow these insights to dictate decision-making — just yet.

You need to dig deeper to identify and categorize consumption trends — relevant to your e-commerce platform — into the following buckets:

• Temporarily postponed: This includes high ticket-value items such as apparel, electronic gadgets, footwear etc.
• Accelerated: This includes daily grocery items, medicines, etc.
• Disturbed: This includes facemasks, gloves, hand sanitizers, etc.

Categorizing these trends will enable you to make clearer distinctions between what your customers consider as “essentials” and “indulgences”. Remember that these customer perceptions are likely to evolve during this period and once a greater semblance of normalcy returns.

For instance: When the lockdown came into effect in the USA, only 13% of households were ordering food online in the first week. This percentage jumped to 38% by the third week. This highlights the changing attitude of customers towards food delivery from an “essential” to an “indulgence”.

2. Identify new buyer personas:

Fact 1: The COVID-19 crisis has reshaped buyer personas that are going to respond differently when the situation begins to normalize.

Fact 2: Based on the value chain in this current scenario, your customers will travel through the following phases towards retention:

After carefully analyzing millions of customer behavioral data points, we’ve identified 5 key buyer personas that are going to drive demand now:

• The Captive Buyer: This type of buyer is reluctant to substitute one product or e-commerce platform with another due to the high cost — in terms of time, effort, and/or money — involved in switching. He/she doesn’t mind postponing purchase based on product availability, last mile delivery capability, ease and familiarity of platform usage, etc.
• The Hoarder or Panic Buyer: This buyer’s demand is not dictated by price but by the more primal emotion of fear. He/she is likely to purchase products in bulk — primarily “essentials” such as groceries, healthcare and hygiene items, etc. He/she is also unlikely to spend too much time and effort searching and browsing for products, which is why you need to offer the most relevant product recommendations ASAP.
• The Price-Conscious Buyer: This buyer display’s maximum loyalty to the price of the products he/she might be interested in rather than your platform or overall customer experience. He/she will be more attracted to product bundles, offers, and discounts that appeal to his/her spending propensity.
• The Hesitant Buyer: This buyer begins with the intention of making a purchase, but is highly likely to postpone or abandon transaction completely during checkout. You need to give this persona confidence in your platform, customer experience, and last mile delivery. An omnichannel marketing approach that allows you to orchestrate customer journeys, nudging them to complete purchase, will go a long way in increasing conversions.
• The Impulsive Buyer: This type of buyer makes snap purchase decisions during checkout and is ripe for targeting with relevant cross-sell and upsell product recommendations. This is going to help you increase your average order value per conversion.

3. Personalize the navigational flow across your website or mobile app:

Fact: It doesn’t matter if your e-commerce website has the greatest looking Home Page or the most visually pleasing app UI/UX anymore. You need to do more. Your customers are unique individuals, so showing the same website or mobile app to both first-time visitors and repeat customers won’t work anymore!

Leverage your customer’s browsing behavior and order history to customize how you want them to navigate across your website. The more customized your navigational journey, higher the chances of you directing them towards a purchase — faster.

You can also experiment with dynamic website elements such as graphics, banner images, and CTAs to optimize the persona-based viewing and navigation experience.

For instance: You can personalize the Home Page viewing and navigation flow across your e-commerce platform depending on whether a new visitor (or an unregistered app user) or a repeat registered customer lands on your website or launches your mobile app.

4. Strategically leverage AI-driven live product recommendations:

Fact: When your customers are active on your website or mobile app, you need to shorten their paths to conversion by giving them product recommendations that are tailor-made to each one of them. And, if you have a large product catalog, then you need AI to do all the heavy lifting, in real-time.

AI enables you to show the most relevant product recommendations across your Home Page, Product Display Page, and Product Listing Page.

You also need to re-order product categories on-the-fly depending upon the search behavior, purchase intent, and historical completed orders on your platform — all to ensure that your buyer personas get exactly what they’re looking for or what they’re most likely to buy — faster.

For instance: To better cater to your new buyer personas and customer segments, you need to deploy AI algorithms that learn from their actions and inactions in real-time to deliver contextual product recommendations on your website or mobile app.

The AI engine learns intuitively and can eventually predict with a great degree of accuracy what an individual user is most likely to click on, add-to-cart, and purchase.

5. Curate a personalized virtual storefront:

Fact: Directing your customers to what they want has to be a relentless pursuit, as part of your larger personalization strategy.

You can climb higher up the personalization mountain by creating a virtual storefront for individual customers. Not only should this contain product recommendations with the highest probability of purchase, it would also continue to get dynamically refreshed based on customer eyeball data.

This means that this specially curated list of products would account for those recommendations that work and those that don’t, and refresh automatically — based on how many seconds a customer spends hovering over an item.

These time-stamped signals loop back into the AI engine, making it smarter, with every interaction that a customer has with your platform.

6. Deliver predictive product recommendations across channels:

Fact: Your AI-led personalization strategy has to extend across multiple channels and devices, even when your customer is inactive on your e-commerce website or mobile app. Well-timed 1:1 customer engagement across digital touchpoints increases the probability of conversions — exponentially.

You need to trigger laser-focused product recommendations across high-impact channels such as email, app push notifications, and web messages.

Here are the kind of contextual recommendations that you can deliver to pursue conversions beyond just your website or mobile app:

• “Suggested for You” Recommendations: These are the best possible recommendations tailored to individual customers based on their general historical behaviour; i.e. product/product categories viewed, items added to cart, purchase, etc.
• “Cart Abandonment Recommendations: These are generated based on the products added to individual customers’ digital shopping carts where the customer may have dropped-off or not completed a purchase
• Buying Pattern Recommendations: These are generated based on individual customers’ most recent product purchases

For instance: If you identify a customer segment that has repeatedly purchased Instant Noodles within the Dry Grocery category and is out of stock due to a demand surge — you can trigger personalized email recommendations updating this segment when the product is back in stock

• Viewing Pattern Recommendations: These are triggered based on individual customers’ most recent products or product categories viewed
• Bestselling Recommendations: These are generated based on the highest selling products on your website or mobile app. These are products that are being purchased the most when compared to other products over a period of time

For instance: In the current scenario, health safety and hygiene products such as facemasks, disinfectants, and hand sanitizers have quickly become bestselling products — over the last 2 months — and will see a steady demand even when the lockdown period is relaxed.

• Trending Recommendations: These are generated based on the most trending products on your website or mobile app. Essentially, these are products whose consumption has shown a percentage increase over a period of time.

For instance: Building on the above example, health safety and hygiene products like facemasks rapidly became a trending product within its category and very soon emerged as a bestselling product, as the COVID-19 turned into a pandemic.

• Recently Viewed Recommendations: These are generated based on the most common products that have been recently viewed by individual customers on your platform
• “New Arrival” Recommendations: These are generated based on the new products that have been added to your product catalog. Our AI engine maps these products to the ones that are most relevant to individual customers and hit upon the ideal recommendations, capable of nudging him/her towards an eventual purchase

Depending upon what channels of customer engagement are working best for which customer segments and buyer personas, you can optimize your multi-channel mix as well as the send-times for these campaigns.

Not only do your recommendations have to be personalized, they also need to be delivered on the right channel and at the right time. And, a robust AI engine facilitates all of this.

7. Harness AI-led product recommendations to manage your inventory effectively:

Fact: Your marketing efforts and inventory management have to go hand-in-hand to increase consumption while driving down overhead costs associated with surplus inventory.

The current COVID-19 situation would have fueled greater demand for certain products while completely eroding demand for other items in your product catalog.

So, don’t just rely on “Bestselling” or “Trending” product recommendations to drive conversions, also account for other products — similar or otherwise — that you can suggest to ease the pressure on your built up inventory.

Incentivize purchase with attractive discounts, offers, and combo deals. It’s a subtle balancing act and operational trade-off, but an aspect of your marketing strategy that requires urgent attention.

8. Deliver the best-possible end-to-end customer experience:

Fact: Customer satisfaction is a function of delivering seamless, reliable, and consistent customer experiences over a long period of time.

While AI-led product recommendations will open up relevance-backed conversion opportunities across customer segments and buyer personas, you still need to get other elements of your value chain just right, such as:

• Seamless website or mobile app UI/UX
• Fool-proof virtual payment gateways and flexible modes of payment
• Sturdy packaging
• Reliable in-time last-mile delivery
• Provision for new-age package collection; eg: contactless delivery

The new rules of e-commerce marketing are already in play. But, relentless focus on the holistic customer experience — backed by personalization — can go a long way in bending those rules in your favor.

Tackling the New Normal…With AI as your Ally

Omnichannel personalization can help your e-commerce brand unlock new waves of user and revenue growth for the remainder of 2020 and beyond.

While customer data and AI will enable you to fulfill latent demand, tap into new conversion opportunities, and turn newly identified focus customer segments into loyalists — don’t be a hard-sell!

At such a time, you need to position yourself as a situation-aware, empathetic, and customer-centric brand. And, not come across as a tone-deaf, opportunistic, and ROI-focused brand.

Disclaimer: This post originally appeared on the Netcore Smartech Blog.

AI-led Personalization: How E-Commerce Brands Can Pursue Growth in a Post COVID-19 World was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

Voted by the Association of National Advertisers (ANA) as the Marketing Word of the Year, 2019 — personalisation is more than just a passing fad that has captured the imagination (and marketing budgets!) of digital brands across the globe.

Your customers need, demand, and expect to be treated as unique individuals. And, as marketers, you need to tailor-make highly contextual and meaningful experiences across the entire customer journey, at every digital touchpoint.

A seamless, customised end-to-end experience on your website or mobile app that anticipates what your customers are likely to click, search for, add to cart, or purchase next becomes the foundation for driving higher conversions and retention.

Trending AI Articles:

1. Basics of Neural Network

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4. Part-of-Speech tagging tutorial with the Keras Deep Learning library

Set in this backdrop, marketers have their job cut out to identify the right vendor to power their personalisation strategies at scale.

While Dynamic Yield has emerged as a major player in this space, there are factors that make it unsuitable, especially for startups and SMBs across industry verticals other than e-commerce.

High cost, bugs with the platform and plugins, lengthy integration times, lack of personalised product pages and personalised search, and gaps in dynamic content reports can be a major turn-off for brands looking to kickstart their conversion growth story ASAP.

But, don’t you worry!

Here are 6 highly rated alternatives to take your personalisation efforts to the next level:

1. Netcore Smartech

A leading AI-powered personalisation and multi-channel marketing automation platform, Smartech enables 5000+ brands to deliver hyper-personalised, contextual, and timely customer experiences at scale.

With Smartech’s advanced solution allows you to go beyond personalising your marketing campaigns, and additionally empowers you to:

· Individualise the website or mobile app viewing experience: Based on their demographic and geolocation data, past search and purchase behaviour, needs, and intents

· Personalise the entire website or mobile app navigational journey: This can include elements such as the product display or listing page, drop-down menu, etc. so your customers find exactly what they’re looking for — faster!

· Embrace the power of patented AI algorithms: To provide the most relevant predictive product or content recommendations based on their probability to search for, click on, add to cart, or purchase high-intent items

And, this is just the tip of the dynamic personalisation iceberg that Smartech can help you with!

You can accomplish the following Smartech:

· Uplift conversions by 8%-13%

· Increase marketing ROI by 16x

· Improve behavioural predictions by 20%-25%

2. Evergage

Based out of Somerville, Massachusetts, USA; Evergage prides itself in its real-time personalisation and Customer Data Platform (CDP) capabilities. Their platform leverages behavioural analytics and ML to deliver 1:1 engagement across channels.

Pros:

· Strong user-level analytics suite

· Good segmentation and targeting capabilities

· Effective A/B testing capabilities for web-based personalisation and onsite messaging campaigns

Cons:

· Heavy focus on e-commerce and retail as an industry vertical

· Complex UI that can take time to get accustomed to

· Limited timely creative assistance and inputs on personalisation strategy

· Pricing model makes it unsuitable for startups looking to scale

3. Adobe Target

A part of the Adobe Marketing Cloud, Adobe Target is an AI-driven omni-channel marketing automation platform. A legacy player in a space catering to predominantly enterprise clients, Adobe Target brings with it its own set of pros and cons.

Pros:

· Customer-level targeting and personalisation can be effectively driven

· Strong predictive analytics capabilities

· Mostly reliable A/B and multi-variate testing capabilities

Cons:

· Works best when integrated with different products within the Adobe Marketing Cloud suite. There remain major concerns around which reporting tool to use or refer to: Adobe Analytics or the one offered by Adobe Target itself

· Non-intuitive UI — particularly for those with no exposure to using Adobe products previously

· High cost of implementation and product, in general

· No KPI-focused approach

· Limited timely customer support that particularly hurts SMBs

4. Qubit

Headquartered in London, UK; Qubit is a personalisation platform that primarily caters to e-commerce brands. They aim to help “e-commerce teams match trading demands with customer affinities to turn a visit into a sale”.

Pros:

· While their platform is primarily built for e-commerce as a vertical, they help resolve strong use cases for other online businesses as well

· Easily navigable UI that allows for rigorous testing

· Intuitive block templates to get started once integration is complete

Cons:

· Integration and configuration can be a challenge in the absence of user-friendly documentation. The process also requires above-average human intervention

· Below-expectation level clarity on conversion reporting and data visualisation

· Limited marketing channel personalisation that can reduce the impact of the individual customer journey towards conversion

· High cost might be a turn-off for smaller businesses looking for a cost-effective solution

5. Optimizely

Optimizely enables businesses to deliver continuous experimentation and personalisation across websites and mobile apps. They help marketers deliver targeted messaging, personalised offers, and recommendations to their customers and users.

Pros:

· Powerful A/B testing-driven platform that attempts to combine human expertise with ML

· Above-average reporting and performance analytics

· Strong online community to help resolve queries

Cons:

· Clear focus on enterprise clients and prospects — reflective in their constantly changing pricing plans. This is a major red flag for a large number of SMBs

· Driving personalisation at scale across a large number of pages on certain websites can produce underwhelming results

· Limited visual data representation while showcasing performance metrics

6. Certona

Certona is a real-time, AI-driven omnichannel personalisation solution. They rely on “predictive analytics and ML to deliver fully-orchestrated customer experiences”. Certona primarily caters to clients in the e-commerce and online grocery verticals and could be a viable option for larger enterprises in these categories.

Pros:

· Strong on personalised recommendations

· Running A/B tests and other optimisation experimentations is easier than other notable alternatives

· Helpful customer success and support

Cons:

· Pricing model may make it unappealing to smaller businesses attempting to accelerate growth through web-based personalisation

· Requires high intervention from your developer team in terms of integration and implementation — this further inflates your operational costs

· Takes almost 10–12 weeks to see an appreciable increase in conversions

Parting Thoughts

Let’s face it — the perfect product doesn’t exist. You need to evaluate your vendor based on the following:

· Monthly volume of traffic on your website or MAUs on your mobile app

· Number of product or content categories

· KPIs you want to impact based on industry benchmarks

· Time and effort needed for integration

· Complexity and flexibility of the platform and resources aligned to its utilisation

· Ability to integrate with your existing martech stack to enable end-to-end customer journey personalisation

· Suitable pricing plans that account for future growth

· Availability of timely customer support

· Time within which your KPIs start moving in the right direction

· Quality of reporting to have complete visibility on the performance of your personalisation experiments

Personalisation is not a linear journey and requires periodic optimisation to boost conversions across your website or mobile app. And, to scale sustainable results, you need to make an informed decision while locking down on a suitable personalisation solution.

This post originally appeared on the Netcore Smartech Blog.

Don’t forget to give us your 👏 !

6 Awesome Platforms that are Acing AI-Powered Personalisation was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

I caught up with Janice B. Gordon, a multi-award-winning Entrepreneur, Consultant, Educator, and Bestselling Author, to get her thoughts on the same. A Sage Top 100 Global Business Influencer, 2017, Janice has over 30 years of business experience, having consulted for high-growth companies across the globe.

Here’s what Janice had to say about how businesses today can deliver superior customer experiences at scale:

Hi Janice! It’s great to hear from you. We appreciate you taking the time to share your insights with the larger sales and marketing community! While the customer has always been king, this becomes far more critical in today’s competitive business environment. What’s your take on the same?

Hi, Pradyut! It’s great to be here!

The customer is still king. However, the tools used to serve the discerning customers’ needs have changed.

We live in an information-rich world but insight-poor environment. Buyers and customers are overwhelmed with the open access information and what they demand is insight. More often it’s the people and not the data that provides this interpretation and insight. You cannot funnel people through processes without providing personality and engagement, personalised to the specific customer preferences.

Marketers today need to focus on gaining actionable insights on their customers’ diverse behaviours across both online and offline channels. Brands will be able to deliver more satisfactory experiences consistently only when they have a unified view of their customers.

How important is it to provide a seamless online and offline customer experience?

Whether it is across offline or online channels, buyers and customers expect personalised engagement, whenever they choose to access your services. Above all, the interaction must be easy and seamless catering to today’s multi-channel and cross-device environment.

Customers now engage over multiple platforms and expect consistency across these platforms and accessible ease of use. Customers do not want fancy bells and whistles; they want ease, and importantly, customers reward those brands, who get it right, with their loyalty.

Having understood their customer-specific preferences, brands need to ensure that advanced data insights are leveraged to the maximum to bridge the gap between online and offline channels. What a brand eventually delivers has to ensure there’s no disparity across both physical and digital platforms.

That makes a lot of sense! In today’s digital era, how can brands adopt a mobile app-first approach to deliver better customer experiences?

Mobile is no longer an isolated channel of customer acquisition, engagement, and monetisation. It has rapidly emerged as the primary choice of customers in connecting all the other channels and available platforms, legitimately linking offline and online.

While this has been true for developed economies for a while now, the rapid adoption of smartphones and improved data connectivity in emerging economies is also fuelling this reality.

Superior customer experience on mobile will deliver the competitive advantage brands are looking for, as this is still a weak link in many brands’ customer experience and value delivery chain.

While creating a mobile-first and mobile-supported customer experience brands must focus on:

1. Creating an app that reflects the parent brand personality and becomes an additional value-driven functional benefit. There’s no point creating an app just for the sake of it. For brands that are mobile-first anyway, focus is easier to maintain
2. Drive easy discoverability and visibility to fuel faster customer acquisition through an effective App Store Optimisation (ASO) and Search Engine Optimisation (SEO) strategy
3. Ensure easier interactions with both mobile apps and mobile sites. For this brands need to adopt a data-driven strategy that places emphasis on customers’ in-app and digital behaviours to craft personalised engagement strategies. Brands also need to seek continuous customer feedback to improve their mobile platforms
4. Optimise for evolving trends such as voice search and the application of Machine Learning to provide highly differentiated customer experiences backed by the power of marketing automation

Do you think brands, today, are adequately leveraging the data at their disposal optimally? What can brands do to improve their data management and analysis?

According to Aberdeen Research, only 15% of organisations are fully satisfied with their ability to utilise data to make informed decisions in managing customer conversations. Then 85% are still capturing and storing information in disparate systems.

In order to deliver exceptional customer experiences, brands require a unified view of individual customers journeys. Using Master Data Management (MDM) and a comprehensive Customer Data Platform (CDP), organisations can eliminate data silos and build consistent, Omni channel interactions with their customers. Brands need to start with the end in mind, the final conversion event.

After mapping the customer journey, brands need to identify what channels of engagement work best with what segments of the target audience.

The objective must always be to leverage data intelligently so that the right message is delivered to the right customer through the right channel at just the right time.

The focus for marketers has rapidly shifted towards Relationship Marketing. How can brands foster deeper customer connections?

People use the same principles to evaluate both personal and business relationships. Customers expect personalised, one-to-one interactions with brands because no one wants to feel like a number or interact with a robot.

Critically, first impressions determine whether or not a brand’s potential customer will willingly become your actual customer. Customer preferences will evolve; therefore, brands must stay close to their customers, to evaluate the variances in behaviour, to adapt, to remain relevant and to grow faster with their most valued and loyal customers.

If brands can succeed in delivering highly personalised, customised, and timely engagement, then trusted customer relationships can be forged at every stage of the customer lifecycle. Engagement strategies would vary for every stage and there can’t be a fix-it-and-forget-it approach.

Brands now want to reach millions of customers across multiple channels such as push notifications, web messages, email, or SMS using marketing automation. What can brands do to personalise their communication to maximise their ROI?

Brands need to accept that they can’t reach millions of customers across multiple platforms with the same message and still expect it to have the desired reach and penetration.

Communication must be tailor-made to customers’ demographic, geographic, behavioural, and device-related data points. The more personalised the brand communication to the targeted profile in the segment, the higher the ROI and better the chances of satisfying customer experience expectations.

Do not PUSH! Brands need to harness smart data to accurately identify customer intent and allow them to “PULL” from your multiple channels. One-to-one marketing offers a proven method to improve response rates and retention rates. Customer segmentation and data mining give marketers the ability to leverage technology and take multi-channel engagement campaigns to an unprecedented level.

Could you highlight some companies, at the top of your mind, that has consistently succeeded in delivering exceptional customer experiences?

At the top of my mind, brands that have succeeded in delivering great customer experiences over a long period of time, pivoting on their engagement strategies, include:

1. Amazon
2. Zappo
3. Dollar Shave Company
4. Ritz Carlton
5. Disney
6. Netflix

All these brands have dedicated a lot of time and resources to truly understanding their target audience, their various personas and preferences. The manner in which these companies are now leveraging the power of AIto strengthen their recommendation engines has also simplified the lives of their customers across mobile and digital channels.

It’s been an absolute pleasure interacting with you, Janice. Thank you once again for sharing some great insights. Any parting thoughts?

Thank you for having me, Pradyut. I’ve enjoyed sharing my thoughts with Smartech.

Every brand has a unique personality as do their customers. One size doesn’t fit all, never has and never will. The world today is connected like never before and mobile is spearheading that convergence. Intelligent data translates into relevant insights.

And, these insights lay the foundation for smarter conversations and interactions, finally delivering superior customer experiences.

This post originally appeared on the Smartech Blog.

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How Can Brands Deliver Personalised Customer Experiences at Scale? was originally published in Marketing And Growth Hacking on Medium, where people are continuing the conversation by highlighting and responding to this story.

How many wellness apps have you seen in the App Store?
You might even develop such apps by yourself. The popularity of wellness apps can be gauged by the fact that self-care turned out to be the app trend of 2018 on the App Store.

Top iOS apps, like Headspace, Calm, Shine, Fabulous, and 10% Happier have extended their offerings from merely aiding sleep and encouraging healthier lifestyles to placing the end users’ mental and emotional well-being at the center of the app experience.

Such apps have successfully adhered to Nir Eyal’s principles on building habit-forming products, leaving users “hooked”, gradually becoming a thread in their daily functional fabric. Let’s now learn how a popular self-care app is using great UX and effective mobile marketing to create a niche for itself.

I am talking about Headspace.
Valued at over $330 million, the app has over 30 million app downloads with over a million paying subscribers. In this guide, you’ll find a detailed breakdown of what Headspace has been doing right to fuel exceptional user acquisition, engagement, monetisation, and retention. These are key lessons that you can repeat for your own app as well.

Lesson #1: Effective App Store Optimisation Strategy

Headspace has been able to ace its App Store Optimisation Strategy (ASO) by working hard on the following components.

(i) App Icon: Headspace keeps things simple with its icon, creating a lasting impression at first glance itself. This must have been finalised after multiple rounds of testing during its early days. Remember that your app logo must create instant brand recall without being “too smart” or overly complex, as screen space is limited post app download.

(ii) App Name and Sub-Title: Just as is the case with Search Engine Optimisation (SEO), it is important for apps to get their keyword strategy bang on, when it comes to the app name and sub-title. This is based on the relevance, difficulty, and traffic of the target keywords. Words that adequately describe your app’s industry, value proposition, and user benefit work best. Headspace gets this right by using keywords that are easier to rank for.

Searching for relevant keywords such as “sleep app” or “meditation app” shows Headspace in the top 2 results in the App Store. In fact, searching for “calm”- a major competitor - shows Headspace on the 2nd position. By including high search volume keywords such as “meditation”, “sleep”, and “breathe” in its app name and sub-title, Headspace achieves higher discoverability and increases the chances of potential users landing on its App Store page.

(iii) App Rating and Reviews: Ratings and reviews serve as consumer word-of-mouth testimonials. These can often make or break an app’s chances of user download.

With an average app rating of 4.7 and a sizable number of ratings provided, Headspace conveys a sense of trust and value, further boosting chances of the app download.

(iv) App Store Page Description and Preview: Headspace uses quirky copy and engaging images, in addition to a video snippet, to effectively communicate the value that potential users would benefit from. This messaging instantly sets itself apart from competition and positions it as a brand that really cares about its customers, wanting them to be better versions of themselves.

By revealing details regarding its different subscription plans, Headspace ensures a high degree of transparency right from the start.

Other important details are the app version and when it was last updated. It highlights the fact that Headspace is constantly working to deliver the best possible user-friendly experience at every stage of the app user lifecycle.

All these factors collectively influence a positive app download decision.

Lesson #2: Easy Onboarding Flow

An effective onboarding flow sets the tone for future app usage. It is your chance to create Aha! Moment during the first time user experience (FTUE). Headspace follows the 3S Principle of App User Onboarding - Short, Simple, and Seamless.

The welcome message - “Show your mind some love” remains static. Headspace makes this stage more engaging with its auto-carousel images that make users visualise themselves in those different situations.

Headspace makes the onboarding process faster by offering first-time users the chance to sign up with an email address of their choice or through social login. Social logins are known to make the onboarding flow more frictionless, reducing the chances of drop-offs by over 55% at this stage itself.

By enabling users to quickly create an account, Headspace captures all relevant personal information to begin creating a user persona at the backend.

The moment a user signs up, he/she is greeted with a personalised message on the next screen, nudging to move further along the usage funnel by gaining greater insights into an onboarded user’s preferences. This lays the foundation for delivering more personalised experiences in the future. Post this, the user is free to explore and experience the app.

What could Headspace have done better? (some tips for your app to perform even better)

(i) Leverage in-app messages during onboarding: Headspace could trigger an in-app message on first-time app launch, encouraging users to opt-in to receive push notifications. This can be made more effective by clearly communicating what sort of content would be “pushed” to users. Eg. mindfulness thoughts, habit-building alerts, monthly subscription payment updates, etc.

Push notifications can increase user engagement by over 85% and user retention rates by 2X, becoming an important channel of mobile engagement in the long run.

(ii) Help first-time users navigate through the app better: Headspace could benefit by offering first-time users helpful simple drop-down tips, directing them to key features and service offerings. This fits into the entire onboarding flow and often fast-tracks the movement of users along the most common paths to conversion.

This is something that Headspace’s competitor, Calm, excels at. Of course, this has to be done in the most non-intrusive manner possible without handholding new users too much!

Lesson #3: Great UI for a Memorable UX

Headspace banks on its unique soothing colour palate and visually impactful caricature-like personas to create a memorable user experience. The app is easy to navigate once you get your bearings straight, reducing the chances of drop-offs.

Unlike Calm that keeps nudging you to upgrade to a paid subscription plan, Headspace allows users to make that decision only when you have experienced enough value through its app.

With a host of self-help modules - ranging from mediation and sleep to personal growth and anxiety relief - Headspace ensures that there is something for everyone. The app subtly nudges users to identify their pain points and start their personal wellness journeys through therapeutic tips, mindfulness recommendations, and audio content.

The element of gamification adds a habit-building dimension to every personal user journey. This helps increase app relaunches, average in-app session lengths, app stickiness, and 90-day user retention in the long run.

What could Headspace have done better?

(i) Offer access to more content for free: Remember the Principle of Reciprocity? By offering up access to greater relevant content and complete app features - for free - Headspace could nurture a stronger relationship with freemium users. This can help in eventually convincing them to become paying subscribers down the line. This also opens up greater monetisation opportunities and reduces the chances of app abandonment and churn.

(ii) Leverage the power of community building: Headspace allows users to “Add a Buddy”, a referral programme that helps with user acquisition. In addition, the app could benefit by helping users build in-app virtual communities (or, groups) suited to their preferences, especially for activities such as meditation, fitness, outdoor sports, stress relief, etc.

This feature could be made more effective by allowing users to join or form communities based on geolocation data and recommendations, creating a greater sense of belonging. While individual self-care goals are important to the overall journey, we, as humans, often derive greater strength in numbers!

Lesson #4: Simple Push Notification Strategy

Given the app category that it operates in, centred around peace of mind, Headspace has made a conscious decision to adopt a very simple push notification strategy. The content is a mix of mindfulness tips, philosophical quotes, habit reminders, health-related recommendations, app-specific suggestions.

While the push notifications are not annoying (Headspace also allows users to manually cap the number of messages they receive in a day), there is a lot of scope for improvement that can optimise Headspace’s mobile marketing spends.

What could Headspace have done better?

(i) Personalise the messaging: Personalising push notification content can elevate open rates by 4X (vs. generic content). It isn’t merely limited to addressing users by their first name. Instead, personalisation involves leveraging a unified view of users to tailor-make content based on their demographic, geolocation, and in-app behavioural (historical and real-time) data and actionable insights.

For instance, a user on his/her meditation journey could receive personalised push notifications such as helpful tips, “pick-up-from-where-you-left-off” nudges, and module updates. All of this also requires intelligent data-driven user segmentation.

Most of the current push notifications are impersonal, driving down the chances of opens and app relaunches.

(ii) Experiment with rich elements: Successful mobile marketing is a lot about A/B Testing and campaign optimisation. Instead of sticking to plain vanilla text-driven push notifications, Headspace could experiment with the use of rich elements such as images, emojis, audio, videos, or GIFs for certain campaigns.

With only 8% of mobile marketers actually embracing rich push notifications, it allows leaders like Headspace in evolving app categories to test the waters. Rich push notifications are known to increase open rates by over 55%.

For instance, users who are harnessing Headspace to regulate their sleep patterns could receive a contextualised rich push notification with a GIF or audio promoting the latest “Sleep Story” added to its library.

(iii) Deliver push notifications in the user’s timezone: With users across 190 countries, Headspace could benefit by improving its user segmentation and delivering messages based on its users’ timezones. Regardless of how personalised and relevant the message content may be; it defeats the purpose if a user receives a push notification when he/she is already asleep!

Headspace could also leverage the power of Machine Learning to optimise its send-times for various engagement campaigns, based on the historical response of its users. A segment of users that has shown a common trend to respond to push notifications at a certain time of the day should be engaged with at this optimal time. This increases the chances of higher clicks and app relaunches.

This can lay the foundation for a more effective predictive app marketing strategy, resulting in higher user engagement and retention.

Lesson #5: Effective Email Marketing Strategy

Headspace recognises the need to use a multi-channel marketing automation approach in order to improve on its key mobile app metrics. Which is why it relies on different engagement channels such as push notifications, in-app messages, and email.

I’ve been particularly impressed by its email outreach, something that definitely gives it an edge over competitors such as Calm. The body content and creatives are quirky and memorable - an effortless extension of its brand persona. This results in better open rates and clickthrough rates (CTRs).

The campaign objective of every email is clear to the recipient with a strong Call to Action (CTA).

For instance, the campaign objectives vary from welcoming new users, nudging them to get started on their individual journeys, and promoting subsidised subscription packages. These are all aimed at encouraging users to relaunch the app and start their individual wellness journey.

What could Headspace have done better?

(i) Leverage dynamic content for personalisation: Personalised emails, based on user’s demographic, geolocation, and behavioural data, could help Headspace boost CTRs by upto 14%. This is based on the same principles as push notification personalisation, but could help Headspace expand its messaging in emails.

(ii) Optimise subject lines and content: Catchy subject lines directly influence open rates. Subject lines offer you a couple of seconds to grab the attention of users. By leveraging Machine Learning algorithms based on users’ historical interactions, email opens, and sentiment analysis, Headspace can identify high-conversion keywords to use in its email subject lines and body content.

Generally, research shows that users are more likely to respond to highly positive or negative keywords, leveraging a sense of FOMO (Fear of Missing Out), especially for promotional content.

(iii) Focus on primary inboxing: When it comes to email marketing, brands will always benefit by delivering their emails under the “Primary” tab instead of the “Promotions” tab of their users’ inboxes. Currently, all of Headspace’s emails go straight to the “Promotions” tab, decreasing visibility, especially in Gmail.

By adopting AI-based dynamic delivery, Headspace could drive up open rates and conversions by delivering a larger percentage of its email campaigns directly into users’ primary inbox. Then again, all of this depends on the multi-channel marketing automation objectives of Headspace!

Final Verdict: You too can build an app to “head” your own “space”

The lessons learnt from Headspace’s UX and mobile marketing strategy highlight how it's important to constantly think about your users.

Do use these powerful tactics to deliver more satisfying customer experiences at scale, especially if you’re working on a self-care app.

Good luck!

Being a mobile marketer is no cakewalk!

Let’s face it. Given the ever-increasing competition across app stores, rising above the clutter to drive app adoption and stickiness is an eternal challenge.

Identifying the right channels to engage with your users in a personalised, relevant, and timely manner assumes incredible significance.

Set in this backdrop, the two most significant weapons at your disposal are push notifications and in-app messages.

What are In-App Messages?

In-app messages are nothing but messages that you can craft and delivery to your users when they are active within your mobile app. Not only does this add another dimension to your entire mobile marketing strategy, but it also enables you to engage with your users in real-time, capitalising on every mobile moment.

In fact, it helps you complement your entire multi-channel marketing machinery, in conjunction with other important channels of communication such as email, browser push notifications, web messages, and SMS.

Are In-App Messages really THAT effective?

Yes!

Let me rephrase that: Indeed. Without a doubt!

In-app messages when used across diverse industries such as travel, food delivery, media OTT, and gaming, have been known to:

• Drive up user engagement by almost 4X
• Produce response rates that are more than 6X when compared to push notifications
• Enhance user engagement rates by 30–40% when used in conjunction with push notifications

Promising, right?

What are the advantages of In-App Messages?

Both as an independent and complementary channel of user engagement, in-app message campaigns bestow some key benefits to mobile marketers, like you:

1. Send messages to your users without an explicit opt-in:
   Unlike push notifications that have an average opt-in rate of 30–35%, in-app messages don’t require your users’ buy in! You can reach your entire user base (broadcast campaigns) or specific sections (user segment-driven campaigns) depending upon your campaign objectives.
2. Harness hyper-personalisation:
   By leveraging your users’ demographic, geographic, device-related data points, you create a unified view of your users. These insights when coupled with their in-app behaviour, actions, and inactions can be used to craft extremely personalised and contextual in-app message campaigns, ensuring that you deliver the right message to the right user, at the right time.
3. Enrich your existing app experience:
   In-app messages give you a chance to embed your engagement communication within the confines of the app universe. Such campaigns become an internal extension of your product, service, or content, nudging users towards conversion events of your choice.
4. Reduce the time and paths to eventual conversion:
   Think of in-app messages as directional markers and milestones, gently helping your new users navigate towards actual conversion. A seamless UX coupled with helpful messages triggered at the right time can help you move users from first time app launch to conversion sooner. Such conversion activities can vary across apps, ranging from a video watched on a media OTT platform, to a ticket booked on a travel app.
5. Leverage the Power of Deep Linking:
   Think of in-app messages as tools of redirection, especially when coupled with relevant and compelling CTAs containing appropriate links that send users to the desired destination within your app or mobile site. This gives you the flexibility to use personalisation as a tool to drive definitive user action.

Excited yet?

What kind of In-App Messages are most effective?

Here are 5 ironclad campaigns that you can run to propel higher user engagement rates and conversions using in-app messages:

1. Welcome Campaigns:

You’ve worked incredibly hard to drive app awareness and have managed to secure user acquisition through app downloads.

Why not express your gratitude by greeting new users with a welcome in-app message, on first time app launch?

This is your opportunity to create the foundations of a lasting customer relationship by creating your users’ first in-app Aha! Moment during the onboarding process. You can send customised messages with simple information on how users can navigate across your app, calling attention to key app features that will help them get started ASAP.

Such campaigns, that aim to establish an instant emotional connect with first-time users, have proven to reduce app uninstalls by almost 20–25% within the first 30 days alone!

Additionally, you can send messages encouraging first-time users to opt-in to receive push notifications, login, complete registration, or update their profiles.

Mind you, users are more likely to enable push notifications if you clearly outline the relevant value they would receive by enabling the same. This shouldn’t come across as a hard-sell. Remember that your users are already sent large volumes of brand communication that is often intrusive and overwhelming! So, tread carefully!

2. First-Time Conversion Campaigns:

While welcoming new users is important, it is even more important to empower this user segment enough to nudge them towards a first conversion event.

Triggering in-app messages offering a promo offer, referral code, first-time purchase discount, etc. goes a long way in incentivising purchase.

This is especially true in the case of e-commerce, travel, ride hailing, food delivery, and payment wallet apps.

Your objective in such a scenario is to quickly convert a new user into a transacting customer that is delighted with a satisfactory first-time user experience (FTUE).

You can add another layer to your first-time conversion campaigns by also automating the delivery of an email to all those users that don’t respond to the in-app message. The idea is to maximise the chances of conversion through a multi-channel marketing automation approach without creating brand dissonance.

3. Promotional Nudge Campaigns:

These are the campaigns where the proof of your user engagement pudding lies, determining the difference between monetisation and app usage drop-offs.

Such campaigns can be used to pitch relevant offers, discounts, time-sensitive flash sales, new cross-sell/upsell deals, etc. either to your entire user base or targeted at specific user segments based on their previous browsing behaviour, purchase history, geo-location, and time zone.

Traditionally broadcast campaigns might produce mixed results. You are in a better position to improve user engagement and resultant conversions by laser-focusing your campaigns at relevant user segments.

These campaigns are most relevant to e-commerce, online grocery, travel, food delivery, ticketing, telecom, and media OTT players.

The objective must always be to contextualise the in-app message so as to personalise the entire end-to-end app usage experience. And, the better you understand your users’ behaviours, personas, and preferences, the better can you tailor-make such campaigns.

4. App/Feature Awareness Campaigns:

The versatile nature of in-app notifications gives you the opportunity to draw attention to new or under-utilised app features, new services introduced, products added to catalogue, content added to library, etc.

The agenda is to educate, inform, and empower your users with enough relevant information to better leverage your app platform, open up monetisation opportunities, increase content consumption, and average session lengths. The messaging would, in turn, differ from promotional nudge campaigns.

Such campaigns can be crafted and run for multiple industries such as e-commerce, banking, travel, productivity, media OTT, music, gaming, fitness apps, etc.

5. Recommendation Campaigns:

Picture a scenario where if you happen to be a media OTT app that offers a live sports streaming section as part of your content library, you want to encourage a specific user segment that watches only cricket highlights to consume more content.

You could trigger an in-app message encouraging this user segment to subscribe to your annual live sports viewing plan for a nominal sum to enjoy the action in real-time!

If you happen to be a travel app, using an in-app message, you can suggest a cheaper flight at a more convenient time to a user who often books tickets off your platform to a particular destination.

All these recommendations are made on the basis of your users’ historical and real-time in-app behaviour and activity. That’s the surest way to contextualise your campaign communication.

Such campaigns work best for e-commerce, media OTT, news, travel, food delivery, payment wallet apps, etc.

Relevant recommendations play a massive role in simplifying your users’ decision-making process by giving them options to exercise that are meaningful.

Your mobile marketing and app engagement strategy is incomplete without in-app messaging added to the mix.

By leveraging in-app messages and push notifications, you can build a double-pronged engagement strategy — both within and outside the app — that helps you boost user engagement and retention sizably.

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5 Best Examples of In-App Messages to Power User Engagement was originally published in Marketing And Growth Hacking on Medium, where people are continuing the conversation by highlighting and responding to this story.

Artificial Intelligence (AI) has made the transition from once being a glorious manifestation of sci-fi imagination to today emerging as a technological reality capable of disrupting industries. In an increasingly hypercompetitive business environment, the marketing function is no exception to the application of AI. In fact, in a recent PwC study, 72% of the marketers interviewed, consider AI as a “business advantage”.

When actionable data is considered the fulcrum for growth, the modern marketer barely utilises 5% of the customer-centric data — that often exists in straitjacketed silos — at his disposal.

This is where Artificial Intelligence Marketing comes into the picture. It is the calibrated use of customer data — from online and offline sources — and computational concepts such as Machine Learning to predict customers’ digital actions or inactions (on web or mobile app platforms), enabling businesses to intelligently target the right customers with the right content across the right channel, and at just the right time.

Trending AI Articles:

1. An intuitive introduction to Machine Learning

2. Decision Trees in Machine Learning

3. The Balance of Passive vs. Active A.I.

4. Mask R-CNN explained

Here are 4 ways in which AI Marketing can be leveraged within the marketing automation ecosystem to craft and deliver highly differentiated customer experiences at scale:

1. Content Optimisation:

If the customer is king, content is your anointed messenger to influence decision-making. AI allows marketers to adopt a data-driven approach with the objective of making predictive sense of their digital customers’ diverse behaviours across channels and devices. By analysing historical browsing and transactional patterns, marketers can identify relevant customer segments.

These segments can be then be targeted with laser-focused personalised and contextualised content through appropriate channels of communication, such as emails, browser push notifications, app push notifications, or in-app messages, to nudge them along their journey towards conversion.

AI further allows marketers to easily embed high-sentiment keywords in these messages that have resulted in a conversion event based on key metrics such as open and click rates relevant to each customer, chronicled over a period of time.

Do they react better to vanilla text messages? Or, do they react better to emojis, images, and GIFs?

Higher the degree of personalisation, higher the chances of campaign success.

For instance, in the context of e-commerce, advanced analytics allows marketers to identify a customer segment that reacts favourably to price drop sales. AI can then help target micro-segments with the right campaign content based on previous products viewed, items added to cart, or purchased.

2. Send Time Optimisation:

Marketers also need to target the right audiences at the right time. AI allows marketers to identify customer segments that respond to a particular campaign at specific times based on historical behaviour. Over a period of time, the system establishes a degree of predictability around the customers’ reactions and this learning input is fed back into campaign intelligence.

Consequently, leveraging the power of AI, marketers can add another dimension of relevance to their multi-channel communication by delivering these campaigns when different customer segments are most likely to respond and act.

Does your customer check his mail between 10AM — 12PM? Or, is he more likely to respond to an app push notification between 4PM — 6PM?

The timelier the customised campaigns, the higher the chances of conversions.

Building on the above example, the price drop campaign would have greater success if delivered to identified customer segments when they are most likely to respond positively in terms of purchase.

3. Recommendation Engines:

Whether it is travel, food delivery, online fashion, or media OTT, today, AI can help marketers make the most relevant product or content suggestions based on their past browsing, purchase, or viewing activity.

This ensures that only those customers that have displayed an inclination towards a particular product category are targeted with relevant or correlated recommendations at just the right time. This opens up multiple cross-sell and upsell opportunities, while helping marketers boost per session length and platform stickiness.

For instance, a media OTT app will recommend a horror film to a user based on his genre consumption history, either through an in-app message (during an active session) or through a triggered email when the film is added to the content library.

4. Chatbots:

A Chatbot is an AI-fuelled software that can interact with humans through a live chat interface. Although at a nascent stage of adoption, the rapid rise of conversational marketing means that over 80% of brands are looking to use Chatbots by 2020.

When programmed to handle standardised queries, these virtual agents extend a high degree of personalisation across web or mobile platforms. The added element of AI enables marketers to customise bucketed responses based on historical interactions with customers, accurately responding to queries, providing suggestions, and redirecting customers through relevant deeplinks.

Additionally, Machine Learning and Natural Language Processing (NLP) algorithms lend a human touch to the conversations, creating a seamless customer experience while driving down manpower costs significantly.

For instance, a Chatbot integrated on a food delivery provider’s platform can be used to render 24-hour live chat customer support based on FAQs pertaining to delivery tracking, order cancellation, refund process, etc. Over a period of time, the Chatbots responses will become more intuitive, refined, and focused, feeding off multiple interactions mapped to individual customers.

The application and benefits of Artificial Intelligence Marketing will continue to expand. With the proliferation of voice assistants and emergence of IoT, brands that carefully evaluate and embrace the power of AI in an attempt to create an integrated, seamless, and personalised customer experience are more likely to reap the rewards of higher ROI, customer engagement, retention, and top-line growth.

What is Artificial Intelligence Marketing? was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

The introduction and application of Artificial Intelligence (AI) in the realm of marketing has spawned the era of the customer-centric data-driven modern marketer. At a time when brands generate gargantuan amounts of customer data that is seldom leveraged optimally, AI comes as a timely shot in the arm for marketers endeavouring to deliver exceptional customer experiences at scale. Prima facie, the computational levers and infrastructure that go behind embedding AI into the paradigm of technology-enabled marketing might seem overwhelming, creating the impression that it is the “machines” that erode the human element, but that’s far from the truth.

AI actually makes modern marketing more human by disrupting traditional monolithic marketing that relied heavily on mass broadcast communication with an inadequate, and often, inaccurate understanding of the target market. These practices relied more on generic trial-and-error where campaigns either created resonance with certain segments or breathed a brand disconnect with other segments, owing to the impersonal nature of the communication.

In contrast, AI enables marketers to make the transition from simply “knowing” to truly “understanding” their customers. Demographic, geographic, and technographic data points can only give one a rudimentary comprehension of one’s customers. It is the in-depth analysis of wide-ranging customer behaviours, actions, and non-actions across both offline and online channels undertaken on multiple devices, that actually shape a 360-degree unified view of individual customers.

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The more marketers comprehensively understand their target customers, their likes, dislikes, and preferences, the easier it becomes to individualize digital marketing campaigns…all courtesy AI.

Over a period of time, AI can enable marketers to gain a sense of predictability around individual customer behaviours, fuelling advanced data-driven customer segmentation efforts, based on pre-defined parameters.

Smarter segmentation, in turn, empowers marketers with insights essential to relevant engagement strategies. Added visibility on the kind of content, device, and channel that resonates with each customer segment, ensures that marketers can now deliver the right message to the right customer on the right channel, at just the right time. Such an approach makes multi-channel marketing campaigns, across both web and app platforms, highly personalised, contextual, and human. Not only do such marketing efforts deepen customer relationships, but they also result in higher conversions, better ROIs, and elevated customer satisfaction and retention levels.

This is also where AI-backed marketing automation comes into play. Marketing automation, as a phrase, is a misnomer, communicating impersonal customer experiences. All it implies is the capability of a platform to leverage AI in order to automate decision-making and execution when it comes to the how, what, where, and when of marketing communication, at every stage of the customer journey.

Right from email subject lines to the images and emojis in mobile push notifications, from the most visually appealing CTAs in in-app messages to the right time to send SMS campaigns, it is the power of customer behaviour-driven AI that can fuel the creation and delivery of 1:1 hyper-personalised customer experiences at scale.

Contrary to fears propagated by detractors, AI continues to usher a new era in data-driven marketing through emotionally intelligent and relevant computing. The beauty of a robust automation platform also allows for AI to continually learn from customers’ evolving behaviours, responses, and interactions; identify hidden patterns, and throw up insights that could eventually be used by marketers to further optimise their marketing campaigns periodically, allowing technology to make customer experiences more reliable, meaningful, and human.

Having said that, it is easy to get swept away in the euphoria that is Artificial Intelligence Marketing. Marketers need to exercise prudent human sense at every stage of automation. Data and insights can only tell one so much. And, not every unearthed pattern or trend needs to be turned into an engagement campaign. There is always a fine line between using AI as an able ally and becoming senselessly dependent on it.

In essence, AI requires a healthy dose of human element to be suitably leveraged, while AI itself can help marketers better understand other humans, i.e. their customers. A martech paradox, if ever there was one!

Can AI Make Marketing More Human? was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

When it comes to your mobile marketing strategy, push notifications constitute your go-to weapon of choice.

But, gone are the days of batch-and-blast campaigns, targeted at your entire user base, that rely on a suspect hit-and-miss approach. An approach often based on ambiguity and assumption.

And, the last thing you want to do as a mobile marketer is to leave anything to chance. Embracing a comprehensive data-driven approach to test what campaign message works on which user segments is critical to ensuring that you effectively scale user engagement and retention.

This is precisely where Smartech’s Mobile A/B Testing feature comes into the picture.

What is Mobile A/B Testing?

Mobile A/B Testing is the calibrated process of comparing two or more variants of a push notification — for a particular campaign — to determine a better performing variant based on key metrics. These include open rates, CTRs, and/or conversions.

Each variant is targeted at a percentage of your entire user base — defined by you — and the winning variant is then sent to the remaining relevant user base.

For instance, if you happen to be a food delivery app, looking to promote a period of heavy discounts this festive and holiday season to your target user base of 1,00,000 active users, you would need to test at least 2 variants of a push notification campaign you plan to send.

The simplest way to go about this is by dividing your entire user base by half, bringing that number to 50,000. Go right ahead and divide this randomly selected user segment by two again. Test both your push notification variants on this segment of 25,000 each. Based on the user engagement and conversion rates, you’ll be able to determine a winning campaign which can then be sent to the remaining 75,000 users.

Sounds simple enough?

It really is!

How do you Setup a Mobile A/B Test?

nstead of working on assumptions, we recommend you follow our 4-step testing process to produce optimal results on each of your carefully brewed push notification campaigns!

Step 1: Establish your messaging hypothesis

Depending upon the type of push notification campaign you want to craft and run — promotional, informational, or transactional — you would have a gut feeling as to what messaging would work best for specific user segments.

Should you focus on plain text copy or complement that with rich elements such as large images, videos, or GIFs? Should your messaging tone be humorous or serious? Should you incorporate emojis or exclude them?

You also need to clearly identify the conversion event you want to accomplish through this campaign.

Do you want to nudge your users to transact more by placing a first time order? Or, do you want to cross-sell a related product?

Step 2: Test your messaging hypothesis

Once you’ve set your hypothesis, begin creating multiple variants to test the same. In fact, with Smartech, you can take your experimentation a notch higher by testing upto 3 variants of the same push notification!

Identify the different user segments — as a percentage of your relevant user base — that you want to target these variants at in order to identify a winning variant. Also, set a time limit within which you want to run this test, depending upon your campaign objectives.

Mind you, all of this can be done effortlessly on the Smartech platform itself with a few clicks!

Pro Tip: While testing your hypothesis, you need to test for only one factor at a time so you get more clarity on what your uplift can actually be attributed to.

For instance, if you’re testing degree of personalisation with the use of emojis at the same time, you will find it hard to identify which variable resulted in better performance

Step 3: Embrace the power of data-driven insights

Allow Smartech’s data-rich insights to corroborate or reject your initial hypothesis based on the performance reports of your tested variants. Smartech eventually helps you trigger the winning variant automatically.

Did your campaign with emojis perform better, in terms of conversions? Well, that’s precisely the one that your relevant audiences are the targeted with, maximising your mobile marketing ROI.

Step 4: Understand user behaviour better and optimise for future campaigns

Remember that the performance of each push notification campaign teaches you something about different user segments. A deeper understanding of your users’ click and in-app behaviour helps you optimise your future data-backed campaigns.

What Factors Can you Run Mobile A/B Tests for?

Let’s now look at the various factors that you can tweak and test for in your push notification campaigns to arrive at a winning variant:

Degree of Personalisation:

As a mobile marketer, hyper-personalising your push notifications is critical to conversion success. In fact, personalising the content of your push notifications can elevate open rates by 4X as compared to generic copy.

While you can personalise your push notifications by addressing your users by their first names, you need to take it up a level by adding a higher degree of personalisation. This would include message content based on your users’ other demographic, geolocation, and historical in-app behaviour.

All of this is made incredibly easy with Smartech’s Unified Customer View that provides a 360-degree understanding of your individual user personas.

Experiment with the degree of personalisation in your variants to identify what resonates best with your test audiences.

Message Copy and Tone:

Gauge whether your test audiences respond better to short and crisp copy or slightly longer sentences with greater details.

Do you grab your test audience’s attention with playful or emotional messaging? Are they nudged towards higher app relaunches and conversions using messages that play with puns and sarcasm or messages that create a sense of urgency?

The experiments you can run are endless and give you immense flexibility to better understand your users’ psychology, laying the foundation for better user segmentation and engagement in the future.

Remember to keep your campaign objectives central to your testing experiments, always.

Emojis:

You’re wondering how the use of emojis can actually positively influence user action!

You’ be surprised! The use of emojis play the role of immediately grabbing your users’ limited attention span, boosting push notification open rates by almost 85%!

This is precisely why you might want to experiment with emojis in your messages. Play around with relevant emojis to gradually hit upon the ones that work best for specific campaigns.

This will help you easily recreate a successful template in the future as well.

Rich Elements:

Push notifications when enriched with rich elements such as large images, GIFs, video, or audio can increase open rates by over 55%.

The ball is in your court to decide what rich elements you might want to include in your push notification variants to be targeted at specific test audiences.

Do your users respond better to an image or a GIF? Delving deeper, do they respond better to a particular image over another one?

Remember that while rich elements make your push notifications more visually appealing and immersive in nature, these elements should be used only when absolutely essential and not come off as being too gimmicky.

Experiment, Pivot, Optimise!

So you see how important experimentation in terms of mobile A/B testing is to your mobile marketing efforts.

Smartech helps you accomplish all this and a lot more, allowing you to focus more on strategy, as our AI-powered platform empowers you to craft and deliver hyper-personalised high-conversion push notification campaigns at scale.

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How to Mobile A/B Test your Push Notifications was originally published in Marketing And Growth Hacking on Medium, where people are continuing the conversation by highlighting and responding to this story.

For digital businesses like yours, your web and app platforms are mere extensions of the overall brand persona, product/solution offering, and customer support. This holds true for a lot of traditional industries such as airlines, telcos, and banking.

In this backdrop, telecom app marketers, like you, have your jobs cut out. Your objectives in this scenario would be the following:

· To establish a channel of self-service engagement that complements the brand positioning

· To facilitate product discovery and user acquisition

· To drive monetisation efforts through mobile channels

The only way you can hope to up your marketing ROI is by getting your carefully acquired users to engage and transact more on your app.

As part of the app user lifecycle for your telecom app, user engagement should remain your north star metric. Engage, engage, and engage with the most personalised, relevant, contextual, and timely multi-channel campaigns to leverage key mobile moments that eventually drive user retention.

Here are 5 messaging campaigns to help your telecom app scale the pinnacle of user engagement, consistently:

1. First-Time Conversion Campaigns

While driving app downloads is critical from a user acquisition perspective, it defeats the purpose if your users aren’t increasing adoption, post download.

Unified customer view allows you to create individual personas including details such as full name, geographic location, mobile number, email address, user category etc. In fact, this comprehensive feature allows you to create a timeline of every in-app activity that your user undertakes.

Using these insights, you can identify specific user segments that have recently downloaded your app, launched it perhaps once, but haven’t made an in-app transaction.

Once such relevant segments are identified, you can then effortlessly craft and deliver effective, hyper-personalised push notification and email campaigns with compelling calls to action and attractive incentives. Your message copy should not sound too promotional as that just comes across as a hard-sell and might turn off new users right at the onset. The idea is to communicate actual value that your app can deliver.

2. Abandoned Cart Campaigns

Almost 40% of users looking to purchase a prepaid recharge top-up, data extension package, special international roaming deal, etc. abandon or postpone purchase at the very last stage, for a variety of reasons.

One way to recapture lost sales is by reaching out to these users and grabbing their attention within an optimal window of opportunity. Such users make up an immediate segment ready for targeting.

This segment of users can then be targeted separately with highly focused and personalised push notifications triggered within 30 minutes of an abandoned cart situation, to increase chances of conversion.

Not only does this remind your users to relaunch the app and complete the transaction, but, it also establishes a reliable mode of automated engagement in the long-run.

You can add another layer of automation to this by triggering an email with the same message to a sub-segment of users that don’t open this push notification. The idea is to eventually identify what is the most preferred channel for outreach for each user based on his/her historical response behaviours.

3. Multiple Transaction Campaigns

Sustainable success is built by repeatedly monetising your active users through focused multi-channel messaging campaigns.

Get users who have transacted at least once to purchase again with timely push notifications and SMS that communicate absolutely meaningful information like bills due, payment confirmation, new data plans, limited-time discounts, convenient payment options, etc.

4. Geolocation-based Campaigns

Create location-specific push notification and SMS campaigns to engage users that travel internationally. For instance, if one of your users is travelling from Mumbai to Madrid, send him a personalised message welcoming him to Spain the moment he lands. Include a backlink to your app, highlighting the local roaming and data charges for his plan.

5. User Feedback Campaigns

A great way to gain insights on your app and service is by asking users for their feedback. Run personalised push notification, in-app, or email campaigns for users who have made at least 3 transactions or service requests to request ratings or reviews.

Honest feedback gives you valuable insights into what your users think of your brand and network. Not only does this help you understand your relationship with your customers better, suggestions and recommendations can also help you rectify app bugs, improve the entire user interface, and deliver more satisfactory user experiences, leading to higher app adoption and retention.

Better ratings and favourable reviews are also likely to positively influence your other network users to download your app off the app stores. More gain for minimal effort on your App Store Optimisation (ASO)!

While driving these campaigns, you do need to be extremely smart about the user segments that you target. Pushing a new user to rate your app when he/she hasn’t experienced enough value off your app will cause more dissonance than benefit. And, that’s the last thing you want!

Never Hang Up on your Users!

Remember that your app will always be an extension of your brand, the network service provider. Never allow either to tarnish your brand image.

Also, note that it is relatively easy to build loyalty for your telecom app, given the fact that the user’s default network will determine his/her download choice. This can also work against you if your network service isn’t up to scratch and the user decides to switch to another network altogether! So, beware!

There’s a lot of scope to experiment with your campaign messaging, content, and creatives to achieve optimal results.

Don’t be afraid of experimenting, based on user behaviour-driven insights, as you strive to deliver differentiated user experiences at scale!

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Dial “E” for User Engagement: 5 Messaging Campaigns to Boost Conversions for Telecom Apps was originally published in Marketing And Growth Hacking on Medium, where people are continuing the conversation by highlighting and responding to this story.