From Data to Insights: Improve, Iterate and Measure

It's a major challenge to drive improved customer experiences and in turn revenue and profitability growth. Why is it that some organisations seem to go from strength-to-strength when it comes to wrangling data for growth whilst others (maybe including yours) is in a state of data despair?

I've got some good news: there are some tangible steps to improve your chances of success!!

In this edition of the Data To Insights newsletter I'll share with you what the best in class are doing to further leverage investments in data initiatives, particularly in the area of Customer 360 for financial services.

First, we have to be clear on the why behind the data initiative. If a team is asking for more leads, then let's be clear on why more leads are required. Is it because the volume or the quality of leads is low, or something else? Does the customer-facing team have sufficient training and software to support timely and effective follow up? Getting a clear why increases our chances of solving the right problem, not just the stated problem.

In one example I heard recently, a request for more leads had been persistent and insatiable for some time. The data team performed a detailed discovery on the why behind the request and discovered that it wasn't a lead volume problem as only 10% of the leads were being followed up. It wasn't a quality problem as the leads were scored using a mutually agreed framework and a suitable proportion were considered to be of high quality. The relationship managers (RMs) were well trained and effective in their roles, so what could it be? As it turned out, the RMs were triaging the leads based on alphabetical order and only getting partway down the list each week. A process change to sort on lead score was a very easy and inexpensive solution when compared to either deploying marketing funds to generate more leads or a new data initiative to uncover new lead sources!

Secondly, ensure collaboration between the data team, business analysis team and the subject matter experts (client-facing team). In the more successful Customer 360 teams we see a recognition that it truly is a journey towards a more complete view in progressive slices. And even with the best foresight we can't predict what data sources, acquisitions, products, regulatory, customer sentiment, or other contextual factors will be at play even only a few months into the future. This demands an agile mode of working with a cultural mentality to fail fast, measure, learn and iterate so we can drive continuous improvement. Having the data team engaged regularly with the business analysts and the client facing team ensures that the different interpretations of the why behind the data can be rapidly understood and new actions for the client team and data team can be agreed for the next iteration.

Thirdly, measure the actions for a full feedback loop for continuous improvement. One progressive financial services firm has their cross-functional team meet every week to go through the data and share their collective interpretation of results. Then, the agreed actions are implemented with specified measures of success applied so that the impact of these improvements can be assessed in future reviews. For illustration, let's say a point of discussion at the data review is to understand which groups of customers are likely to experience mortgage repayment stress given recent inflation and the threat of interest rate rises. The data team takes the ownership to deliver an actionable insight for potential missed payments. The nudge will be a task to call the client, placed right there on the customer record in the CRM (or alongside a core banking system or other if necessary - you can read more about this here). In a subsequent cross-functional meeting the uptake and performance of the recommended actions (nudges) is reviewed. The reasons why recommendations were or were not followed and the client outcomes are fed back into the process so that future insights continue to improve. One additional strategy is to apply an A/B testing approach to help assess which recommendations are more effective (recommendations for a homogeneous cohort are varied between two groups - and the results are contrasted).

Using these three steps (get to the why, ensure collaboration and measuring the actions) you can better manage the end-to-end value chain of data initiatives and improve your return on investment. Whilst there are many other factors at play, having this foundation allows you to anticipate, manage and improve each week which is of major importance on the journey towards Customer 360. Similarly, this approach will help you find your first true win which will spur on further success and investment in your customer data initiatives.

What are your tips for driving better customer experiences through data? Have you tried any of the steps above and what were your findings? I'd also love to hear from you about what you might like to read about in future editions of this newsletter - we have a very experienced data team across a number of industries and business challenges, so let's go on this journey together!

Kind regards,

Andrew Aho

[email protected]