Big data is of big importance. It has been for years. But in 2021, we’re going to see marketing teams especially focused on taking control of customer data and analytics efforts for the welfare of the enterprise.
Case in point: Research shows it’s four times more expensive to get a new customer than it is to keep an existing one. Still yet, not all current customers are created equal. Some are small spenders. Some are high-value targets. Understanding where and how your market segments out will be crucial to ensuring profitability in the coming year. And honestly: forget about growth. I’m talking about survivability. At this point in pandemic, closures are still a real risk for many companies. And CMOs everywhere will be working to avoid them. Over the past several months, I have been outspoken in sharing key trends for digital transformation in 2021. Many of the trends revolve around big data, analytics, machine learning, and AI. I have also been an advocate of enterprise investment in customer data platforms. This growing category is seeing widespread adoption, and investment due to the need to enrich the customer journey and utilize vast data that spans far beyond what exists in our systems of record—This is why Microsoft, Salesforce, Adobe, Oracle, Twilio, SAP, SAS, Treasure Data, and so many other tech giants have gone long on CDPs.
The key though, isn’t just having the data, but using it intelligently and effectively to better understand your customers, opportunities, weaknesses, financials, and risks. If you’re a CMO or involved in leading the implementations in analytics to deliver stronger performance for your organization, focus on the following for 2021.
Use Data to Segment for Loyalty
As noted above, it’s far cheaper to keep a current customer than it is to find a new one. That’s why CMOs across the board will need to focus on ways to improve customer loyalty moving into 2021. How does that translate to data? For one, it means you may need to consider capturing new metrics to determine who your most loyal customers are. It also means that when you find that data, you’ll need to work in tandem with customer service to illustrate to those customers that you understand and appreciate how loyal they are. It means far more to me when a customer service representative thanks me for being a customer for 15 years than it does to get a 10-percent-off email they send to everyone and their brother. So, use your data to learn more about who your loyal customers are and what makes them stick with you—and do more of that.
Use Data to Segment for Value
Like I previously mentioned, not all customers are created equal—not even loyal customers. Some may pay for services as they need them making it an operational expenditure. While others may buy full packages and make it a capital expenditure. That’s why segmentation is so incredibly important. Yes, all customers are to be valued. But not all customers bring the same value to the company. As marketing teams, it’s essential to focus the most time and effort on those that pay dividends.
Use Data to Improve Profitability
It’s expected that 1 in 4 CMOs will invest in consent and preference management software in 2021. How does that impact profitability? For one, it will help you capture even more granular insights and target more accurate messaging. For instance, if you collect an email from every person visiting your website, the chance that each of those visitors will convert to a sale is incredibly small. If you focus instead on those that spend time to share their user preferences, shed light on their use cases for your products and services, and let you know how and when they like to be contacted, you’ve already improved your potential conversion rate. That, in turns, creates more profitable sales teams. On another note, it’s been noted that CMOs should begin (if they already haven’t) elevating the capture of those insights to an automated, AI-driven system or platform. There simply isn’t enough time or human power to capture insights any other way. Furthermore, data can be deployed effectively to optimize pricing data and there are tools that can take this to the next level for businesses looking to squeeze the most revenue out of every sale. Pros, Inc. is an example of this. The company uses data and AI to optimize pricing in many industries, most notably the highly complex pricing associated with seats on an airplane. This is finding its way into more and more industries and yielding greater profit out of every sale as perfecting pricing is often a neglected consideration, but data should do away with the uncertainty and lost profit opportunities that can be realized through data.
Use AI to Keep Data Safe
With so much more data flying around, it’s essential to be more careful with it. Doing so will also improve profitability by decreasing risk. This includes things like processing data closer to the source via edge computing and using tools smarter than humans to protect it, wherever it is. In fact, some 40 percent of privacy compliance tech will rely on AI by 2023. There is so much data in most enterprise systems, moving, processing, storing, etc., that it will also be key to use AI (and common sense) to determine which data, if any, you simply don’t need. This will save money in storage costs, as well. This will also become an increasingly important component of doing business. Customers will expect more from their vendors, both B2B and B2C in terms of protecting data, and affording customer privacy—AI, observability, and SaaS tools form the likes of Datadog, Splunk, and RSA will enable this for more businesses,
We say it often, but 2021 will be the year that the use of data will separate the leaders from the followers—or at least the survivors from the lost causes. Companies that collect and use data successfully will survive exponentially longer (and in the future, grow exponentially faster) than their non-data using counterparts by better targeting the right customers, making the right business decisions, and saving money when it comes. When CMOs and enterprise leaders use that data to gain the right insights for the enterprise, everyone wins.
