Data is a pretty powerful concept. You could say it’s every brand’s hidden super power. Yet, there’s so much talk about the power of data, but in reality, there isn’t a lot of actual “doing”. It’s like a super hero full of promises of integrity and the common good who never gets asked to join the good fight. Companies have good data intentions, but fail to execute.

The fact is - data are hard. Hard to collect, resource and time intensive to manage, require hand-holding given inconsistencies, exception reports, IT priority lists and the myriad of different databases – with no unique customer ID. And, then once you have the data in one place, things get even more complicated. There’s so much data. Where does one begin understanding, segmenting, prioritizing, avoiding the mine fields of bad data that create bad marketing, actually generating relevant dialogue?

It’s OK to start small – as long as you (1) collect data that’s clean and (2) actually use those data to be relevant in your marketing. Identify the top 5 data points that are most critical to your marketing and your customers. Put the processes in place to collect the data, to validate it, and to refresh it on an ongoing basis. Then, put it to use. Start testing different ways to use it to target, message, personalize and measure response. Modeling aside, there are few brands that regularly use more than five data points in their marketing. So even if you start small, your marketing is already positioned to be smarter than most brands. As your marketing matures, so will the sophistication of your data use.

1. 360 View of the Customer

After the small start, the goal is to create a 360 view of the customer. Technology and processes are getting better, making it easier to collect data. However, the types of data we can collect are ever expanding. Rich data via only one channel is just as limiting as marketing in only one channel. Most customers have just one relationship with your brand. In return, they expect brands to have one relationship with them, not a different relationship by channel or one that recognizes just half of how they interact with you. The types of data you want to collect include:

  • Payment Transactions: How, what, when, where do they buy from you? The industry is getting a grasp on this, starting to use this data category at a macro level.
  • Engagement Data: Social, mobile, gamification, etc. have highlighted the importance of gathering (and understanding) data about how customers interact with you when they aren’t buying. Yes, this is social/mobile, but also includes things like opt-in, advocacy, ratings & reviews, customer service, talking and looking, but not buying, marketing response and more.
  • Customer Profile: Data that help us understand explicitly and implicitly who these customers are and what kind of relationship they want with our brand. This includes self-reported data (i.e., preferences, contact data, opt-in profile), appended data (i.e., demographics, psychographics, modeling scores, life stage), but also inferred data (i.e., what they click on, types of tweets, willingness to game, reason codes at the call center).
  • Data from Every Channel – The Easy Ones and the Hard Ones: Creating the 360 profile is a progression for most companies. Starting with the easiest channels, then working to less trackable channels with less defined interactions (i.e., opt-in profiles to payment at POS to advocacy via social). This isn’t just purchases and marketing response, it’s support tickets, returns, repairs and more. Just because it’s hard, doesn’t mean it shouldn’t be done.

2. Using the Data to Drive Relevant Communications

While it is important to compile data at every touchpoint, it is equally as important to use the data you do have in a smart manner. As with any super hero talent, so it goes with data: with great power comes great responsibility. Don’t ask for customer data, then not act on it. It’s a missed opportunity with the customer at best, and a break in your customer promise at worse.

  • Use data to benefit your customers as well as your business. Customer data should enable brands to market from the customer’s perspective, not to just better target the brand’s marketing calendar.
  • Back off; Embrace niche marketing. One of the hardest things for brands to do is to not send every message to every customer. Investing in data-driven marketing means that customers aren’t going to hear every single message, a hard concept for most organizations to accept.
  • Don’t over do it. Subtle works sometimes, too. There’s a thin line between “big brother” and “a brand that gets me”. Your communications don’t have to shout “We have your data!” to be effective, but should use the data to make it easier for customers to get a relevant message.

So, who is doing it well?

For data collection – American Express is top of the list.

American Express has long boasted one of the most robust customer databases in the world, with deep transactional information across all customer spending areas. Not one to sit on its laurels, Amex has aggressively been moving beyond transactional and demographic data - long time Amex assets - to include social and channel behavior toward building a truly 360 view of their customers. And while there’s still improvement to go, Amex is using that data aggressively to drive card usage, brand image and better customer relationships.

For most brands, understanding customer’s preferences via social channels is still an unknown world. Unlike most brands, Amex is aggressively building the foundation and database to learn more about each customer across channels, particularly social. In return, they get rich data on consumer behaviors, a test bed for creating relationships via social, and happier cardholders with stronger Amex relationships. Consider these examples:

For data usage – it’s Amazon.

Amazon’s data aren’t as broad as American Express, but they use the data so well.

  • Relevance: Of course, this is at the top of our list. It’s only too obvious to say that Amazon’s marketing goes beyond the typical personalized messages to provide spot-on recommendations. Its recommendations and ratings & reviews have single handedly proven out the business case for investing in tools that get customers to do something other than buy.
  • Utility: Not just relevance, Amazon’s also brings value and utility to its marketing by bringing relevant messages that make segments act. Hallmarks include Amazon groups (i.e., Amazon Mom, Amazon Student) tailored to each segment’s value equation, and Amazon tools (i.e., tool bar wish list, mobile price check).
  • Consistency: Relevance is Amazon’s trademark, but this is due in part to the consistency with which they are relevant. For too many companies, data-driven marketing is a one-off promotional effort rather than a way of life. The approach will create a better performing promotion, no doubt. But, it stops short of create a customer relationship that’s stronger than a competitive offer.

Data-driven relationship marketing is a concept that has more than arrived that starts with data collection and usage. It’s complicated – and it’s not. It doesn’t require some hidden super hero talent, spandex leotard or flowing cape. It’s about thoughtful customer strategy and deliberate consideration of data and process to create marketing from a customer perspective – the difference between mild-mannered marketing and brands that can move mountains.

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