Use Data Analysis to Boost GrowthApril 20, 2017
By Tim Keith
Core data analysis isn’t just for the banking giants. Community and regional banks have more to gain from data driven marketing.
Community and regional bank marketing teams often miss out when it comes to utilizing core data—and it could be costing them big money. Many banks just assume that their marketing plans are successful, or that they need a multi-million-dollar marketing budget to take their marketing programs to the next level. As a former banker, I understand the fear of taking a risk when trying something new. But, with careful analysis of core data, small to mid-sized banks can more accurately direct their marketing efforts to drive growth without breaking their budget. And I would strongly urge bank marketing teams to become more familiar with this concept.
Here are the key steps banks need to know to build a successful data driven-marketing program that directly connects to the bank’s larger strategic objectives:
1. Identify customer base segments.
For all the talk in the industry about relationship banking, most institutions are still product driven organizations. This product orientation flows downstream from ALCO committees to marketing teams, and inevitably leads to marketing programs that cast too broad a net. It centers the focus on product features and benefits, rather than customer financial needs.
The reality is that customers have a variety of financial needs that ebb and flow over time. This makes segmentation fundamental to any true relationship strategy. The building blocks of any successful segmentation methodology are capacity and propensity. In other words, a customer must have the basic means to buy a product and at least some inclination to do so.
2. Analyze household data.
Once the marketing team has adopted a solid foundation for segmentation, a household data analysis should be conducted. Household-level analysis forces the banker out of product-silo based analytics and into a view of how consumers generally think about their banking relationships. This type of analysis provides key product usage and profitability statistics. And, when done correctly, it clearly identifies the strengths and weaknesses of the bank’s customer base. Marketing programs built on this foundation are more likely to leverage the strengths of the organization while bridging the gaps within the bank’s product mix, sales, and delivery channels.
3. Conduct an opportunity assessment.
An analysis of your bank’s household data only goes so far. How do you really know if your statistics are good or bad—or ultimately how your customer base differentiates? To answer these questions, you must bring in normative peer-group data for comparative analysis. The biggest challenge is to find normative data that is reliable and relevant. Normative data sets must be comprehensive enough to be reliable statistically, but also built around categories that are meaningful to your business.
For an example of what a good normative analysis can reveal, look at single-service households. Every banker knows they have single-service relationships—and that those relationships offer some degree of cross-sell potential. But, how do you go about quantifying that potential in key cross-sell categories? A normative assessment provides benchmarks that help quantify the opportunities in accounts and balances.
4. Develop and implement a strategic marketing approach.
Once your bank has completed an opportunity assessment, you can develop a strategic, multi-channel marketing approach based on the opportunities identified by the data. Targeted messages resonate more effectively because they are based on financial relevance to the customer. Properly targeted consumers are more likely to respond to specific, timely messages and self-identify with the products being marketed.
The assessments remove guesswork associated with marketing planning, and they provide consumers with viable financial solutions that address their particular financial needs. And, by understanding, anticipating, and speaking to individual customer needs, data-driven marketing ultimately enhances the bank’s brand perception in the communities they serve.
5. Track the campaign results.
It is hard to overstate the importance of tracking campaign results. Despite this obvious assertion, tracking is often the first thing to move down the list of priorities for many banks. Effective tracking should be more than just counting widgets. It should evaluate the impact of product sales on underlying customer relationships. This includes an analysis of how net inflows and outflows of balances within a customer relationship correspond with campaign response balances. Tracking is another area where peer group normative data can be indispensable to evaluating the performance of a campaign. Ultimately, campaign tracking must provide a basis for a reasonable marketing ROI calculation and answer the question, “What would I do different next time?”
Data analysis has been around as a tool for banks for nearly 30 years, but many institutions never get actionable value out of investments in this area. When done properly, a data-driven approach to marketing allows community and regional banks to compete more effectively against larger mega-banks by being true to the idea of relationship banking. I have seen small to mid-sized banks achieve tremendous growth in a short span of time from data driven marketing campaigns. For many banks, adopting a data-driven marketing program isn’t anywhere near as much of a risk as the status quo.
Tim Keith is a former banker who in 2007 co-founded Infusion, a provider of data-driven direct marketing campaigns that generate strategic growth for community and regional financial institutions. He works directly with financial institutions to implement data analysis services, support marketing efforts, write and present comprehensive customer analysis, evaluate campaign results, and design strategic growth programs. Email: email@example.com