Personalization in Retail and CPG
Hey (fill in your company name), do you even see me?
The priorities of consumers have shifted drastically. Companies need to step up their game to create deeper, more relevant, and inclusive consumer interactions. The new consumer preferences, behaviors, and habits will last beyond the pandemic. What should you consider as you improve your personalization capability so that you won’t be left behind in 2023?
I know, I know… Marketers especially have been shouting from the rooftops about the importance of being more relevant and targeted to enhance individual consumers’ experiences for a long time. As a consumer, you feel some progress — but frankly, not even remotely as much as you suspect technology and analytics should enable. And the gap between companies that embrace personalization and those that see it as more of a check-the-box exercise becomes increasingly pronounced. COVID-19 was an accelerator for the need for personalization. Why? Limited store experiences and more online shopping showed the art of the possibility of personalization across a good amount of eCommerce businesses.
Three-quarters of consumers switched to a new store, product, or buying method during the pandemic.¹
Well, there you have it. Three-quarters of consumers! If this doesn’t
motivate you to step up your personalization efforts. How about this:
Seventy-one percent of consumers expect companies to deliver personalized interactions. And seventy-six percent get frustrated when this doesn’t happen.¹
To ensure you and I are on the same page, here is what I mean when I say ‘personalization’: Personalization refers to tailoring marketing messages and strategies to individual consumers. The goal is to create a more relevant and engaging consumer experience, which drives sales and profitability.
So, what building blocks are required to enable personalization? Before we look at the three pillars, I want to highlight one essential prerequisite for making this successful: Personalization is not a marketing-only problem. Personalization is also not a challenge for the analytics department to tackle independently. Personalization is an organization-wide opportunity to lean into collaborating across functional silos.
The names of the pillars change slightly, depending on whom you talk to or what the most recent buzzwords in the marketplace are, but essentially you have the following; I’m using McKinsey terms as they resonate with me the most:
1.) Opportunity Identification
2.) Activation and Optimization (at scale)
3.) Martech and Data Enablement
Keep in mind that given that there is much organizational orchestration required to improve across the three pillars. Therefore you need to develop in parallel a straightforward way of working across the organization and also develop your process of upskilling the employees — these items I will need to tackle in a separate article at a later time. Let me know in the comments if you’d like to see it sooner rather than later.
Opportunity Identification
Developing a holistic view of the consumer, often known as a 360-degree view, is the foundation for producing deep and targeted insights. Using granular data from observed behavior, engagement, preferences, and attitudes will help you identify opportunity pockets within your customer base. It’s fascinating how data can be stitched together to give you a deeper insight into your shoppers and whom you’re serving.
Gone are the days when you could rely on a few large macro segments that were singularly focused, such as a breakout by demographics or attitudes alone. Today, you have little excuse not to go from macro to micro audiences to create personalized experiences for your consumer. You do this based on various factors, such as price/promotion sensitivity, category/product preference, store/channel preference, historic/predicted value, and many more. Connecting all these attributes across the consumer and finding pockets of consumers who behave or are predicted to behave in the same or similar way establishes your micro-segments. These can be used to zero in on your company’s value, short or long-term.
By empowering the marketer with data-driven insights, you receive a significant advantage in flexibility in selecting and measuring target groups and contacting them at various stages in their journey as you build out your intended experiences. You will be able to tap into new growth possibilities that will promote retention and lifetime value by capitalizing on this data-enabled capacity and strategically applying it throughout your consumer engagement initiatives.
Activation and Optimization
Based on your Opportunity Identification, you should now have a good sense of where to start. Now it’s all about continuous investment in Test & Learn and investing in automation to scale. Testing (again, a topic that requires a series of articles) is key paired with establishing a robust measurement process as you finetune your personalization efforts across your consumer base. The findings will then be used to improve your interventions.
Where to start? When deciding how to craft your consumer experience, you essentially start with the end experience in mind. How do you want the consumer to feel? Then, you work backward to the signals that trigger the singular or the series of activations. Now you can craft a positive, engaging experience for your (prospective) consumer that aims at getting the right message to the right consumer with the right tone at the right time, using the right touchpoint. Depending on where you are in your journey with personalization, this could sound quite daunting. As with all significant challenges - have a clear objective, break it into sub-goals, and chip away, one day at a time.
Thankfully, these are not manual interventions anymore, as you build models and scale them to run ideally in or near real-time. With that, you can have thousands of permutations and experiences run in parallel, providing highly targeted and personalized consumer encounters.
As you can imagine, an incredible amount of development has been made in this space, where you can purchase out-of-the-box SaaS or work with your Data Science team to build custom solutions. Content never seems to be the bottleneck. Depending on the maturity of your organization, tagging and centralizing the content might require some work. If this is the case, you can create more personalization by focusing less on serving personalized content, and more on personalizing when and how, and to whom you serve the existing content (time of day, day of the week, marketing channel, sequence of the marketing channels, etc.).
Martech and Data Enablement
As mentioned, building the data foundation for the marketing technology stack (martech) needs a clear and robust data strategy. That means there is a clear explanation and use for each level of data, be it zero-, first-, second-, or third-party data. CPG companies have historically depended on 3rd party data because, for the most part, they lack direct interactions with the consumers — so collecting 1st party data and looking to scale has not been an accessible option. The landscape is changing substantially as privacy laws are gaining more traction, and trends like the ‘cookie-less-future’ are being enforced, where marketers cannot use cookies on Google Chrome. With that, companies need to decide on their data acquisition strategy and whether they want to invest in 0-party data, a way to collect information directly from your end consumer. Connecting all the data is not done overnight and requires considerable thought and testing — but don’t let perfect be the enemy of good, and you have to start somewhere.
It’s easy to get overwhelmed by the offerings in the martech space. I did some research and found close to 10,000 solutions. One thing I’ve done in the past is work with the teams to understand the most critical use cases we want to enable. Once you have those figured out, it’s substantially easier to search for solutions to help your consumer with these vital experiences, allowing you to stagger the investment and not get shut down by the board or CFO. A good starting point then will be whether a direct connection with consumers will give you a good enough return on investment — you have the option to consider building out your own consumer-data platform (CDP), which, although quite a challenge, could provide a substantial competitive advantage in the mid to long run. A CDP frequently holds elaborate and complex consumer data sets and sends relevant messages based on your developed intelligence engine. All to aim at delighting the consumer and forming a more robust relationship through getting closer to delivering the right content and using the right touchpoint at the right time to individual consumers.
How you go then about pillars like digital asset management (DAM) platform or product-information-management (PIM) system will heavily rely on your specific priority use cases and experiences you want to unlock for your consumer.
Remember, three pillars that enable personalization — Opportunity Identification, Activation & Optimization (at scale), Martech & Data Enablement. Being clear on the critical use cases and experiences you want to enable will allow you to progress across all three items in a deliberate and focused way. Don’t leave your personalization up to chance:
- let the business lead,
- liberate and connect your data,
- and empower cross-functional work.
As always, curious to hear your thoughts, experiences, and comments. Reach out if you want to learn more through Linkedin.
All that’s left to say is: Hey (fill in your company name), do you see me now?
