5 Data-Driven Marketing Catalysts for 2016 Growth

The new year tends to bring renewal and the promise of doing something new, better and smarter. I get a lot of calls looking for ideas and strategies to help improve the focus and performance of marketers’ plans and businesses. What most organizations are looking for is one or more actionable marketing catalysts in their business. To help you accelerate your thinking, here is a list of those catalysts that have something for everyone, some of which can be great food for thought as you tighten up plans. This year, you will do well if you resolve to do the following five things: Build a Scalable Prospect Database Program. Achieving scale in your business is perhaps the greatest challenge we face as marketers. Those who achieve scale on their watch are the most sought-after marketing pros in their industries — because customer acquisition is far from cheap and competition grows more fiercely as the customer grows more demanding and promiscuous. A scientifically designed "Prospect Database Program" is one of the most effective ways great direct marketers can achieve scale — though not all prospecting databases and solutions are created equally. A great prospecting database program requires creating a statistical advantage in targeting individuals who don’t already know your brand, or don’t already buy your brand. That advantage is critical if the program is to become cost-effective. Marketers who have engaged in structured prospecting know how challenging it is. A prospect database program uses data about your very best existing customers: What they bought, when, how much and at what frequency. And it connects that transaction data to oceans of other data about those individuals. That data is then used to test which variables are, in fact, more predictive. They will come back in three categories: Those you might have “guessed” or “known,” those you guessed but proved less predictive than you might have thought, and those that are simply not predictive for your customer. Repeated culling of that target is done through various statistical methods. What we’re left with is a target where we can begin to predict what the range of response looks like before we start. As the marketer, you can be more aggressive or conservative in the final target definition and have a good sense as to how well it will convert prospects in the target to new customers. This has a powerful effect on your ability to intelligently invest in customer acquisition, and is very effective — when done well — at achieving scale. Methodically ID Your VIPs — and VVIPs to Distinguish Your 'Gold' Customers. It doesn’t matter what business you are in. Every business has “Gold” Customers — a surprisingly small percentage of customers that generate up to 80 percent of your revenue and profit. With a smarter marketing database, you can easily identify these customers who are so crucial to your business. Once you have them, you can develop programs to retain and delight them. Here’s the “trick” though — don’t just personalize the website and emails to them. Don’t give them a nominally better offer. Instead, invest resources that you simply cannot afford to spend on all of your customers. When the level of investment in this special group begins to raise an eyebrow, you know for certain you are distinguishing that group, and wedding them to your brand. Higher profits come from leveraging this target to retain the best customers, and motivating higher potential customers who aren’t “Gold” Customers yet to move up to higher “status” levels. A smart marketing database can make this actionable. One strategy we use is not only IDing the VIPs, but the VVIP’s (very, very important customers). Think about it, how would you feel being told you're a “VVIP" by a brand that matters to you? You are now special to the brand — and customers who feel special tend not to shop with many other brands — a phenomenon also known as loyalty. So if you’d like more revenues from more loyal customers, resolve to use your data to ID which customers are worth investing in a more loyal relationship. Target Customers Based on Their Next Most Likely Purchase. What if you knew when your customer was most likely to buy again? To determine the next most likely purchase, an analytics-optimized database is used to determine when customers in each segment usually buy and how often. Once we have that purchase pattern calculated, we can ID customers who are not buying when the others who have acted (bought) similarly are buying. It is worth noting, there is a more strategic opportunity here to focus on these customers; as when they “miss” a purchase, this is usually because they are spending with a competitor. "Next Most Likely Purchase" models help you to target that spending before it’s “too late.” The approach requires building a model that is statistically validated and then tested. Once that’s done, we have a capability that is consistently very powerful. Target Customers Based on Their Next Most Likely Product or Category. We can determine the product a customer is most likely to buy “next.” An analytics-ready marketing database (not the same as a CRM or IT warehouse/database) is used to zero-in on the customers who bought a specific product or, more often, in a specific category or subcategory, by segment. Similar to the "Next Most Likely Purchase" models, these models are used to find “gaps” in what was bought, as like-consumers tend to behave similarly when viewed in large enough numbers. When there is one of these gaps, it’s often because they bought the product from a competitor, or found an acceptable substitute — trading either up or down. When you target based upon what they are likely to buy at the right time, you can materially increase conversion across all consumers in your database. Develop or Improve Your Customer Segmentation. Smart direct marketing database software is required to store all of the information and be able to support queries and actions that it will take to improve segmentation. This is an important point, as databases tend to be purpose-specific. That is, a CRM database might be well-suited for individual communications and maintaining notes and histories about individual customers, but it’s probably not designed to perform the kind of queries required, or structure your data to do statistical target definition that is needed in effectively acquiring large numbers of new customers. Successful segmentation must be done in a manner that helps you both understand your existing customers and their behaviors, lifestyles and most basic make up — and be able to help you acquire net-new customers, at scale. Success, of course, comes from creating useful segments, and developing customer marketing strategies for each segment.

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5 Data-Driven Marketing Catalysts for 2016 Growth

Mike Ferranti

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