In my previous article on personalization, I discussed why financial service providers are moving towards delivering personalized customer experiences and why those experiences can drive higher business value and customer satisfaction and engagement. Most financial institutions are still engaged in mass “push marketing” – communicating the same generic message to all customers, at a time when the needs of customers are becoming ever more diversified, unique and real-time. Financial institutions (FIs) are trying to figure out how to change their customer experience models from “Pushing Campaigns” to “Predictive Servicing.”
Personalization in banking is not primarily about selling. It’s about providing service, information, and advice, often on a daily basis or even several times a day. Such interactions, as opposed to infrequent sales communications, form the crux of the customer’s banking experience.
In this article, I will discuss how financial service providers approach personalization and I walk you through a framework we use with customers to first assess their personalization maturity level and then devise a plan to achieve true contextual personalization to maximize the highest customer engagement and value.
STAGE 1 – Static-Based Campaigns (Personalization = 0)
Many financial service providers continue to rely on Stage 1 type marketing, pushing the same message to everyone with no content variety. In this stage, FIs generally lack a.) the analytical capability to use data to segment their customer base and/or b.) the ability to deliver variations in content to customers.
There is zero variation in the content or messaging that customers receive. Content is changed on a mass level and distributed to everyone. Accordingly, the process can be labor intensive, resulting in low customer engagement and very little ROI for the organization. More or less spamming, or spray and pray as a strategy!
STAGE 2 – Simple Rules-Based Campaigns (Personalization = Infancy)
In this stage, FIs generally have simple analytics capabilities, but the data is not real-time, nor does it include a wide set of parameters for segmentation. Additionally, FIs have basic tools such as content management systems to create variations in content and to orchestrate content messaging with segmentation rules. Data analysis to identify the best segmentation parameters is most likely a manual process, with long processes for rule adjustments and re-calibration of rules and outcomes. Marketeers, IT and data analyst resources have to come together and spend time connecting the dots to roll out a one-off campaign.
The most widely adopted technology in the MEA region is sending an SMS notification to a large segment of users and hoping the short messages are timely, relevant and will yield results. Some service providers also use push notifications to inform consumers of offers, events and services.
I would consider Stage 2 type personalization as a unidirectional push with low engagement and conversion rates and a minimal improvement on Stage 1.
STAGE 3 – Model-Based Campaigns (Personalization = Elementary)
With improved data analytics, FIs use a wider set of parameters (but still limited) to perform segmentation. They typically use batch data that may be a few weeks old, but incorporates information such as demographics, products purchased, and credit history. Segmentation models are developed to support a few business objectives, like getting customers to sign up for a special offer.
Here, content management systems do have more capabilities to allow variation in messaging, but still lack complete integration with segmentation data feeds to orchestrate the delivery of content. At this level, manual intervention is still required. For example, delivering an in-app offer may require code changes or manual entry into a push notification platform where target user data is manually uploaded from the output of the analytics platform.
STAGE 4 – Integrated Interactions (Personalization = Comprehensive)
A much wider set of data parameters is used here to perform segmentation, mixing batch and real-time data. Hence, the size of the target audience for a particular piece of content becomes smaller, but yields higher relevance and customer engagement. Data elements such as spend behavior, user’s location, proximity to branches and merchants, products subscribed or rejected, spend categories and app/website clicks are all used to narrow down what advice, nudges, or services might be more relevant for the user segment.
A more sophisticated content management system integrated with segmentation data is used to orchestrate the delivery of user engagement resulting in an evolution from “pushed” one-time campaigns to interactive, “always-on” experiences.
This is when a mobile banking app or website starts to behave differently depending on the user by displaying services, insights and nudges that are most relevant to that individual.
For example, the next time you book a flight or arrive at the airport and happen to have a credit card with lounge access privileges, your bank app might remind you, through its app engagement, to avail your benefits. This is meaningful engagement that customers expect.
STAGE 5 – Interaction Orchestration (Personalization = Predictive Servicing)
At this stage, a wide range of real-time data feeds, combined with ML models, are used to dynamically predict the user’s preferences and life moments, and to prioritize the delivery of insights and recommendations such as best offer or next best action.
Communications are defined by interest, interactions (past & present) and orchestrated decisioning which are delivered at the right time, in the right moment. FIs engage with the customer on an interactive basis, leveraging model optimization and response messaging. Data is seamlessly pulled in, feeding segmentation rules, while ML models are periodically retrained and fine-tuned. The orchestration layer combines all inputs to trigger omni-channel delivery of content pulled from the content management system and delivered to the right channel.
For example, during a visit to an auto dealer you have previously visited several times in the past 3 months to test drive cars, you receive a prompt from your mobile banking app based on the dealership you are at – special rates on car loans at Mercedes or trade-in incentives at Prius or cashback offers from Toyota. This is Stage 5 personalization – smart, relevant and timely – an orchestrated engagement.
Which stage is your bank at on the maturity personalization curve?
Most FIs in the Middle East and Africa that I do business with are at Stage 2 or 3, with aspirations to move up the curve to Stage 4 or 5. How do they get there? To accomplish this goal and go beyond, the data assembly components, content management system, and decision orchestration process must all be integrated to work in tandem. In addition, delivery channels such as internet banking, mobile apps, customer service call centers, and chatbots must all be integrated backwards with the personalization platform in order to generate engagement content that is relevant to the channel.
So what does your institution need to do to level up? More on this in my next blog.
I look forward to your comments and insights.