Jane wants to buy a TV and starts her shopping journey with a Google search. She finds an electronics review site, clicks on a banner ad, reads about the product details, and decides to go into the store to see the model. She speaks with a sales associate and posts a picture of the TV on Facebook for her friends’ feedback. She also uses her smartphone to do a quick price comparison, and scans the QR code to get additional product information.
Welcome to problem #1 for retailers: The company knows that a potential customer has interacted with it across a lot of touch points but it has no idea that all these interactions are with Jane. It can track each of these interactions across touchpoints, but doesn’t know how to tie them to an individual customer. Since each touchpoint yields a particular piece of data, this becomes a complex data management challenge.
Retailers are desperate to unlock this intelligence so they can make more personalized offers. Research shows that personalization can deliver five to eight times the ROI on marketing spend and lift sales 10% or more.
Here are four keys to tracking today’s multichannel customers.
Many companies assign unique customer IDs but lack a systematic way to enrich them to form an integrated view of the channel-surfing customer. A systematic approach requires you to identify and evaluate all of the touch points where you interact with a customer. Too many retailers miss out on valuable insights by stopping at either the data that’s at hand or data that is already easily matched with a customer, such as purchases across multiple credit cards. When building your enriched customer views, start with priority customers or segments (big spenders, loyal spenders, future spenders, and so on).
Focus on the important data
Even though your goal is to track all touchpoints, don’t try to harness 100% of the data. Most companies already have plenty of customer data, but don’t tie it together to create a richer picture of their consumers. In our experience, the most fruitful insights come from combining transaction data (such as purchase amounts over time), browsing data (including mobile), and customer service data (such as returns by region). Focus on data that will help you achieve specific marketing goals. For example, if you need to build customer loyalty, concentrate on gathering data from post-purchase touch points like customer service logs or responses to up- or cross-sell emails.
These data rarely exist in one place in the organization so you’ll need to pull in people from multiple functions such as marketing, sales, in-store operations, IT, and beyond. We’ve seen companies create small “SWAT” teams that assemble people from these functions to break through bureaucratic logjams.
Fill in the data holes
There are three main types of external data sources that can be invaluable. Following are examples of each – but these just scratch the surface.
Data you can buy
Broad census data from companies like Experian or Axiom can match hundreds of public and private sources to identify consumers, for example through credit card matches or telephone numbers.
Panel data from companies like Nielsen and Compete provide access to a full set of customer actions of about 2 million people. These provide granular views of the customer, such as records of every web page visited and consumer purchase made over a one to two year period.
“Traveling cookie” data build a digital footprint of a consumers based on their logins at popular sites (for example, on airline sites or Facebook). Once the customer logs in, the cookie follows that customer wherever he or she goes on the web. Datalogix aggregates data across hundreds of logins and matches it back to a database of more than 100 million households. This connection helps marketers identify consumers on their own sites and others’ and link sales to prior behaviors.
Data you can request from customers
Retailers should encourage customers to self-identify by logging in to the website, using a loyalty card in store, or identifying themselves when calling customer care. Gap, for example, will always ask for your email address when you buy a product. Other companies provide mobile coupons in exchange for cell numbers.
Data you can partner for
Companies with complementary data sets can combine insights by partnering. Vendors such as Visa have partnered with retailers to introduce highly targeted location-based offers to consumers as they make purchases. Scan your Visa at a Gap to make a purchase, and get offers on your smartphone for retailers within walking distance.
Match the data with the customer
This wealth of data is only useful if you can build the complex algorithms needed to connect data collected from these streams to your unique customer IDs. You’ll also need IT systems that automatically update a customer’s profile each time he or she interacts with you at a given touchpoint and scrub the data to ensure accuracy (e.g., validating emails). The organizational and technology challenges are significant, and we have touched on only a few of them here. But we’ve seen big pay-offs for retailers who can follow individual customers across media and channels. Increasingly, such a capability is not just nice to have; it will be essential for any retailer who hopes to stay in the game.
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