Data and analytics is exploding.
Whether you call it big data, business intelligence, or analytics, it is clear that the use of data is going to be critical to any company’s success. Especially in the bank and credit union industry, data and analytics is a relatively new concept. Sure, data has been used in the past but never has it been so critical to sustainable operations.
With the growing adoption of data and analytics, the bank and credit union industry is reaching a critical juncture. In a previous post, we discussed how data and analytics will become a competitive necessity – not a competitive advantage – in the very near future. If you believe this to be true, two questions immediately arise:
1. In what ways can we use data and analytics?
2. Once we know what we want to do, how do we actually do it?
Over the next few weeks, we will be releasing several posts that primarily address the first question. Specifically, we will be addressing question 1 from several different executive perspectives. The ways that a CMO (Chief Marketing Officer) would use data and analytics might differ from how the CLO (Chief Lending Officer) or CFO (Chief Financial Officer) would use data and analytics.
Five Ways CMOs Can Use Data
In this post, we identify five ways that CMOs can use data.
1. A/B Testing
With the analytics now available from sites like Google Analytics, HubSpot, and MailChimp, data is readily available for website traffic, conversion rates, click-through rates, and a variety of other data points that are a gold mine for marketers.
A/B testing allows marketers to compare two versions of something (a site or page design, email content, offer, etc.) and measure the results of the user experience and interaction. For example, you could use A/B testing to determine which email subject line generated more opens or which content led to more conversions.
The ability to tweak content to users while using data to support your decisions allows marketers to gain valuable insights and deliver more successful messaging to consumers.
2. Customer/Member Segmentation
We have already discussed member segmentation in a previous post, but its value to marketers cannot be stated enough. Through data and analytics, marketers can understand the channel usage, product propensities, and a variety of other details about specific segments of their customer base/membership.
Does the millennial want the same user experience as the retired baby boomer? Certainly not; it is important to understand these differences and create an experience that is most beneficial to that particular segment.
With the growth of non-traditional financial institutions like Ally Bank, a 100% digital bank, or Lending Club, a peer-to-peer lending platform, CMOs in the banking industry will need to use data and analytics to deliver the proper experience and messaging to the appropriate segments.
3. Channel Analysis
There is some overlap between channel analysis and customer/member segmentation, but, with the digital growth of the financial industry, channel analysis is deserving of its own section.
Who is contacting your call center? Who hasn’t completed an in-branch transaction throughout their entire customer/member lifetime with your FI? These are the types of questions CMOs must ask and data and analytics can answer. Asking these questions enables the CMO to define the proper growth strategies based on the underlying data.
4. Measuring Consumer Sentiment with Social Media
Facebook, Twitter, Instagram, LinkedIn and the multitude of other social media networks can offer a wealth of information about consumer sentiment. With each new post about your bank or credit union, you can gain a more complete picture of the consumer’s feelings towards your FI. CMOs can use data from social media to gain insights that would ordinarily require surveys or focus groups to gather. These insights can be gained more quickly and efficiently with new technology.
Several companies now specialize in analyzing social media posts to determine consumer sentiment towards a branch or product. These insights, when combined with data from previous marketing efforts and internal operations, allow a CMO to identify and address flaws in product, services, or messaging quickly and efficiently.
Analyzing social media posts and the associated text is considered “unstructured data”. The key difference between standard business intelligence and big data lies in big data’s integration of unstructured and structured data sources. Organizations that can leverage social media information can accurately state that they are using big data in their marketing efforts.
5. Tracking and Measuring ROI
Have you ever watched Shark Tank? How often do you hear Mark Cuban ask an entrepreneur “what is your cost of customer acquisition”? Can your bank/credit union get this metric? Can you get it quickly?
CMOs can become their CFO’s best friend by combining financial data with their marketing information. Tracking average conversion on marketing campaigns combined with product and service profitability data, you can create realistic ROI models for finance to evaluate marketing activities. Overlay this data with the strategic growth objectives of the bank/credit union, and your models and forecasts will improve significantly.
The ability to measures and track success with your campaigns enables you to learn from each marketing effort. Even some of the other techniques mentioned in this posts, like A/B testing and monitoring social media sentiment, can be combined with campaign tracking to improve the likelihood of success for future efforts.
What does this all mean?
The US Navy SEALs have a saying, “slow is smooth; smooth is fast”. For data and analytics in organizations, it can be said like this: “small steps lead to small wins; small wins lead to big wins”.
CMOs can use data to drastically improve marketing efforts. In their positions, they have the ability to drive data and analytics initiatives by applying some of the way to use data we have suggested in this post. Marketers should start by taking small steps with data and analytics. These small steps will lead to small wins. But, after a few small wins, some big wins will emerge. Like a flywheel, its challenging, at first, for data and analytics initiatives to gain momentum. But with some small wins and a good data strategy, your data and analytics initiatives will gain momentum. Once it gains momentum, those small wins will have led to big wins and your organization will be on its way to becoming data-driven.