One of the most valuable assets in your business is data - data about your customers. Effectively leveraging this data can have a significant impact on growing revenues.
In the post that follows, we’ll recommend five things to turn your customer data into business growth, and we’ll address three common concerns.
Concerns about data
1) “I don’t have much data.” We hear this one so frequently that my colleague Knight Stivender wrote a whole blog post about it. Typically, clients with this concern are talking about one of two things: 1) They don’t know the identity of their customers, or b) They don’t have a lot of additional information about their customers other than, say, a name or a transaction history.
You do have to know at least some of your customers to follow our five suggestions, but it needn’t be everyone. Perhaps you have a loyalty program that includes a segment of your customers or an email signup list. While not perfect, you can use a known segment of your customers as a proxy for your customer base. In terms of how much you know about your customers, no worries. With simply a name and address or an email address or a phone number, you can append a wealth of household-specific demographic and behavioral data. And if you don’t know how best to do it, we can help.
2) “My data is not clean.” No business’s data is 100% clean, but we do usually find that our clients’ data is not in as bad a shape as they think it is. We can help with a variety of hygiene and correction routines to improve companies' data quality. It’s not a reason not to leverage your customer data.
3) My data is too sensitive to hire someone else to help. Some industries - especially healthcare and financial services - have stringent regulations and security issues that make it difficult to seek data support from outside companies and contractors. But while the vendor approval process can be a cumbersome one when it comes to anything involving data security, most providers who work in this space are well accustomed to dealing with these sorts of issues and are set up to handle privacy and security with detailed support.
Suggestions for leveraging data
1) Match transactional data to individual people. Often a business’s customer data is at a transactional level. For example: Jane Doe bought a widget on June 2 for $50. If so, you may not know if Jane has bought multiple times, how recently, if she’s bought other products from you, how much she’s spent in aggregate, and so on. In order to understand Jane Doe the customer, you need to have someone append your transactional data to individual customer data to create what's known in our business as a "householded" view.
2) Understand geography. Geography doesn’t get enough attention in most businesses' marketing. Too often, marketers think of their trade area in terms of specific counties or zip codes — or, in some cases, in terms of a radius around their location (e.g., a five-mile radius). In fact, your own customers should tell you your effective trade area. Measure your customer penetration by zip code or other geography, or plot your customers and create a custom polygon that represents your effective trade area. Rarely will the effective trade area be a circle (e.g., a five-mile radius). Natural and man-made boundaries, traffic patterns, competitor locations, and other factors have a significant impact on convenience and trade areas.
3) Understand your customer profile. It’s vital to profile your customers and understand their defining demographic, behavioral, and attitudinal attributes. How old are they? How much education, income and wealth do they have? How do they lean politically? What hobbies do they have? What magazines do they subscribe to? What other sorts of things do they purchase, other than your own products and services? Remember, you need not to have collected this data yourself. It can be appended from other sources with simply an address, phone, or email. (This is what we do every day.)
4) Segment and cross-sell. It is less expensive to sell another product to an existing customer than to win a new customer. Businesses should look first within their own customer base to identify prospects for additional revenue. Apply a meaningful segmentation scheme to your customer base including Recency, Frequency, Monetary Value, and Product Category, and then cross-sell and upsell.
5) Employ look-alike modeling. By analyzing your data and building a statistically sound predictive model, you can focus your acquisition efforts on those prospects with the highest likelihood to become customers.
Want to learn more? Schedule a free data consultation with our data scientists and we'll offer suggestions specific to your business.