Revolutionizing Banking via Omnichannel Hyper-Personalization
How do you feel as a customer when you receive an Excel mail merge-type email from your financial service provider with no product or service information/offering remotely connected to your need? As a financial firm, do you think just addressing your customer via mentioning their name in communications, looking at them in a grouped way, and providing them product recommendations sans context is going to win their loyalty? If the answer is no for both, read ahead!
Without throwing the numbers, online banking customers (which are majorly GenZ and Millennials) now use multiple channels unlike before for engaging with financial firms. Also, they are more prone to switch to a new firm or select a firm that provides them with context-based products and services, one that is tailored to them and solves their problem. Customer focus has shifted from “solve my problem” to “provide me a world-class experience while you solve problems for me”.
That’s why Omnichannel Hyper-personalization is a hot topic in banking right now. This system listens to their current and potential customers, curates real-time personalized products & services at the segmentation of one, and provides them with a seamless and integrated experience across multiple channels, such as online, mobile, and in-person to drive purchases, increase engagement, enhance CX, and yes, develop loyalty.
The approach focuses on providing financial services by leveraging the latest technologies to deliver a highly personalized and seamless banking experience across multiple channels. This approach is designed to meet the needs of customers who interact with their bank in a variety of ways, from traditional in-person interactions to digital channels such as online and mobile banking.
What is this Omnichannel Hyper-Personalization: There are 3 integral, & interconnected cogs in the system which come together to make wonder happen:
- VoC (Voice of Customer): Listening to the voice of the customer which relies on customer feedback/query data collection, active customer listening to understand the sentiments, trends, perceptions, and needs.
- Hyper-personalization: Relies on customer’s browsing activity, actual purchasing behavior, customer’s affinity, and active times & leverages advanced analytics & AI to provide advanced, real-time personalization & focus on customer’s emotional state.
- Omnichannel delivery: Relies on customer interactions across channels, integrated channel architecture, and database for real-time data sync to provide customers with a seamless and integrated experience across multiple channels to create one unified platform for the customer.
But what values and benefits it creates for the banking ecosystem: Omnichannel hyper-personalized banking can provide a plethora of values to the customer, a few of which can be seen in the below picture:
Banks can reap the following benefits by embracing Omnichannel Hyper-personalization, such as:
- A better understanding of customers: By collecting data across multiple channels, banks can gain insights into their customer’s needs and preferences, which help them to identify new opportunities to serve their customers better.
- Provide a more personalized experience for their customers: Banks can tailor their products and services to meet their customers’ individual needs and preferences to increase customer satisfaction and loyalty.
- Effective management of customer interactions: Banks can easily track customer interactions and respond more quickly to customer inquiries which help banks to provide a better customer experience.
- Increased efficiency: By streamlining their processes, banks can reduce costs and increase efficiency to increase their profits and remain competitive in the market.
- Seamless experience across different channels: Customers can move seamlessly between different channels, such as online banking, mobile banking, and in-person banking, without experiencing any disruptions or having to re-enter information via technologies such as APIs and data integration platforms that allow different systems to communicate and share information.
- Context-based financial products and services: Banks can increase customer loyalty and reduce customer churn as customers who feel that their bank understands and caters to their specific needs are more likely to stay with that bank for the long term.
- Increased upselling/cross-selling: By providing personalized recommendations and offers, banks can increase cross-selling and upselling opportunities.
OKAY, but what challenges banks can face while embracing this? : There are a few challenges banks should be wary of before deciding to opt for Omnichannel Hyper-Personalization, which are given below:
a. Collecting customer data across multiple channels can be difficult due to legacy systems.
b. Banks need to ensure that they are collecting accurate and up-to-date data, which can be challenging and time-consuming.
c. Banks should have the right technology in place to store and analyze customer data. This means investing in the right technology to ensure that they can store and analyze customer data quickly and efficiently.
d. Banks must use customer data ethically by collecting and using customer data under applicable laws and regulations.
e. Banks must provide a secure and reliable experience for their customers & ensure that they are providing a personalized experience for their customers by reaching segmentation at one.
So, the bank has weighed the benefits and challenges and now wants to pursue this, how will that happen: Implementation of Omni channel hyper-personalized banking focuses on touching each step of the customer journey and finding insights.
The steps and their detailing are as follows:
Step 1: Decide Business Goals — The extent of implementation depends on the business objectives as the implementation of sophisticated tools can be costly. Hence, the company must first decide its target customer audience followed by its engagement channel, and ultimate goal (engagement, increased CX, acquisition, etc). Once the goals are decided, the company must decide the KPIs and metrics to determine the progress & success of their strategy.
Step 2: Gather real-time customer information from all channels (legally) — Banks should collect and analyze data on customer behavior and preferences across all channels, including online banking, mobile apps, and in-branch interactions. This data must be analyzed to gain insights into customer behavior and preferences, and then to use this information to personalize interactions and offers.
Step 3: Segmentation at One — Banks should segment their customer base into groups of one i.e. generate insight for individual customers based on demographics, behavior, and other characteristics to create personalized communications and offerings.
Step 4. Create Targeted Customer Journey — Once the segmentation at one has been achieved, the next step is to curate the customer journey where each step can be influenced via data-backed offering to enhance customer experience. This is the major step as it has the potential to convert a non-user to a loyal customer. Balance in terms of nudging and pushing must be achieved. The equal focus should be given to the pre-purpose, purchase, and post-purchase stages.
Step 5: Distribute across all channels uniformly and take feedback — Banks must integrate all channels and ensure that customer data is available in real-time across all channels. This can also be used to provide customers with easy-to-use self-service options such as chatbots or virtual assistants, to improve the customer experience and provide personalized assistance. Users must be incentivized to provide feedback and banks can use customer feedback to optimize their personalization strategies and improve the overall customer experience.
Use cases for Banks: There are several examples of hyper-personalization in banking.
A. Customer who frequently purchases beauty products online may receive personalized recommendations and promotions for similar products through email, social media, and in-store displays. This not only makes their shopping experience more convenient but also increases the likelihood that they will make a purchase.
B. If a customer contacts a company’s customer service through social media, the representative can quickly pull up information about the customer’s past purchases and preferences to provide more efficient and effective assistance.
C. If a customer has previously shown an interest in a particular product on a website, they may receive targeted email or social media ads for that product or receive personalized product recommendations when they visit the website again. Additionally, if the customer has previously had a positive experience with a brand’s customer service on one channel, they may receive priority service on other channels.
D. Customers may begin their journey on a brand’s website, where they browse products and add items to their cart. The brand can then use data from that interaction, such as the items the customer viewed and added to their cart, to personalize their experience on other channels.
E. Brand can use collected data to send personalized email or SMS promotions for related products or to show personalized product recommendations on social media. When the customer is ready to make a purchase, the brand can also use this data to pre-populate their information in the checkout process, making it faster and more convenient.
F. If a customer contacts customer service with a question about a product they recently purchased, the customer service representative can quickly access their purchase history and provide more accurate and helpful information.
Other indicative use cases are:
Let’s talk about the technological part; Technology forms the backbone for delivering an omnichannel hyper-personalized experience to customers. Banks can use artificial intelligence (AI) and machine learning (ML) technologies to analyze customer data & use predictive analytics to better understand their customers. Finally, banks can use data analytics technologies to analyze customer data to gain insights into their customers’ needs and preferences. This can help them to identify new opportunities to serve their customers better.
Solutions for any enterprise range from a simple chatbot integration for smart resolution for customers to a complete overhaul of the platform via developing a CXM/CDP platform. This provides the facility for the enterprise to access and pick solutions as per the organization’s goals.
Some of the major enterprise solutions for delivering omnichannel hyper-personalization are given below:
- Unified Cross Channel Platform — Use of a single, cloud-based platform to deliver all customer services/queries uniformly across multiple channels.
Cloud Contact Center: Handling customer queries from any channels where all channels are hosted on an internet server-based platform, leading to increased agent performance & better data analysis
Integrated Query Platform: On-premise or Cloud-based solution for managing customer queries coming from multiple channels at one unified platform
2. Automated Support — Auto resolution of queries via a holistic knowledge base of information captured across channels.
Conversational Chat: AI-Powered solution to understand customer query intent & provide resolutions of simple/ repetitive queries by leveraging a knowledge base
3. Data Intelligence — Generate insights using data captured from multiple systems across channels to build an integrated customer and/or operational view
Cross Channel Customer: Analytics Integrates customer data currently present in siloes to provide a 360 view degree view of customers and derive actionable insights from captured data for customers across the journey
Agent Performance Analytics: Provides visibility into the overall performance & improvement of agent key skills including key areas of development
4. Agent Assist Platform — Deliver a consistent and personalized by providing targeted inputs and assistance and thereby improving their efficiency
Sentiment Analysis: Leverage technologies such as NLP or text analysis to extract the mood of the customers
Next Best Action: Quickly navigate multiple systems to proactively deliver information to the agent on the different actions that can be taken for the specific customers to resolve the query.
Visual Assistance: Use of video chat feature to provide customers with real-time sharing of content/challenges for a richer and more targeted customer experience.
5. New Age Training — Deploy new age training approaches to upskill & prepare people to manage the requirements and complexities of an omnichannel environment
AR/VR-based training: Leverage immersive technologies to create an engaging training experience for BCs/Agents
Simulated training environment: Train agents/BCs on customer interactions using real-life scenarios within a controlled environment
6. Design Thinking — Use of structured framework to assist enterprises in identifying technology/solutions to create maximum impact on user experience.
Customer Journey Mapping: Breaking down the customer’s journey based on multiple factors into discrete steps to identify key friction points and drive meaningful engagement to increase CX
7. Data Platforms:
CDP (Customer Data Platform) — Packaged software that creates a persistent, unified customer database by pulling PII & first-party data for each customer that is accessible to other systems & uses analytics to aid in personalization& predict customer engagement. CDPs pull together customer demographic, behavioral, and historical data, mostly via APIs from internal and external sources.
CRM (Customer Relationship Management): CRM is used to manage any organization’s interactions with potential & existing customers. Focusses on client relationship with the organization via customer journey with the organization A CRM system stores customer data from different channels, including all points of contact between an organization and its consumers, mostly first-party data
8. Customer Experience Platform
CXM/CEM (Customer Experience Management): CXM is used to understand as well as influence customer perceptions regarding a business & its products at the various touch points of the customer journey. Qualitative in nature and focus on customer feedback & preference to provide a personalized experience. Mostly used the data from CRM for analysis and giving out insights.
CCM (Customer communications management): Strategy to improve creation, delivery, storage, and retrieval of outbound communications, including those for marketing, new product, renewal notifications, claims correspondence, documentation, etc. Customer interactions can happen via a range of media & output, including documents, SMS, and Web pages
Apart from this, there are other solutions like Marketing Automation Platforms (MAP) which help businesses to automate and personalize marketing activities, such as email campaigns and targeted advertising & Personalization engines which allow businesses to create personalized experiences for customers across different channels, such as web, mobile, email, and in-store. Product management tools like web personalization and A/B testing tools can also allow for real-time personalization of the website and mobile app experiences.
Summing it up, Omnichannel banking and hyper-personalization are important strategies for banks to remain competitive in the market. However, implementing omnichannel hyper-personalization can be challenging for banks. Banks need to ensure that they are collecting accurate and up-to-date customer data, have the right technology in place to store and analyze customer data, are using customer data ethically, are providing a secure and reliable experience for their customers, and are providing a personalized experience for their customers. If banks can overcome these challenges, they will be able to provide a more personalized and seamless experience for their customers. As technologies continue to evolve and customers’ expectations continue to change, we will likely see more banks adopt this approach in the future.
