When retailers think about big data, the cost and complexity of sifting through the wealth of structured and unstructured data to make intelligent decisions can often seem overwhelming. But at its heart the key to unraveling big data lies in finding a common thread between context, content and customer satisfaction. This thread isn't sewn neatly across a straight line. It loops and turns and changes direction, following non-linear paths as unique as each of your customers and prospects.
So how do you connect these three critical components? It starts with a hard look at your data. If it’s been awhile since you de-duped and cleaned up your organization’s database, now is the time to do it. After all, how can you target someone with a great offer if you don’t know how to reach them? Your data needs to be both accurate and actionable to drive relevant, favorable and valuable customer engagements that lead to stronger, long-term relationships. Only after you’ve cleaned up your dirty data can you turn to the three “C's” to enhance the modern customer experience.
Context: Combine Individual Behavior Patterns and Macro Consumer Trends
A disconcertingly high percentage of companies still lack a full, 360-degree view of the people who buy their products and services. They’re stuck in the old-school mindset of measuring specific stand-alone campaigns in isolation — rather than looking holistically at the performance of all touch points across the entire consumer decision journey. But doing so, they’re missing out on critical consumer context (try saying that three times fast!).
The ability to quickly assess individual behavior patterns and current, macro consumer trends, and marry the two together in real time is essential to uncovering valuable context to help you make decisions. This context can then be use to serve up tailored content where each customer prefers to research products or services, connect with brands, and ultimately, make their purchases.
A simple example might look like this: If retailer REI collects the data that customer “Jim” redeemed a direct-mail coupon for 20 percent off his purchase and bought new skis and the following year, Jim buys a new ski jacket online. It’s clear that Jim is an avid skier and a repeat customer who trusts your product and buys it via multiple channels. A critical component for talking to Jim will be seasonality, level of expertise and – perhaps – if Jim is of an age where he might have children or other family members who ski. Collecting this type of information and making sense of it would help REI understand what Jim might need and value now, and predict what he might need 5 years from now.
Content: Create, Organize and Curate
Consumers have endless purchasing options. Successful retail marketers know that it’s not enough to just “push” information out about how great their products or services are – they have to continuously add value by highlighting review information, providing in-the-moment offers, actively engaging in online conversations, etc. And this all begins and ends with relevant, meaningful content.
To do this effectively – and in a scalable, sustainable manner – existing datasets must be matched with a contextual marketing module that includes systems for engagement. This will allow you to create, organize and curate content that can be delivered to consumers through the right channels at the right times. For example, if Jim is incredibly active on social media and often posts content related to skiing – perhaps Jim could write a guest blog for your website in exchange for some new bindings. Now Jim feels important, valued and his brand advocacy increases dramatically. Or maybe Jim would simply value recommendations for the best mountains in his area. Next year, Jim will likely need new bindings or boots and a coupon might be just the thing that brings him back into your store.
Customer Satisfaction: Measure to Close the Marketing Loop
Efforts to modernize your marketing processes are meaningless unless you have a mechanism in place to calculate your “Net Promoter Score,” or a numeric “grade” representing the willingness of customers to recommend your products or services to others. This also allows you to assess how people are responding to the campaign efforts you’re putting forth. And by feeding this data-backed intelligence back into the context phase, you can continuously refine and enhance your approach over time.
Jim is obviously interested in the products you sell. Understanding who he is and what he values are very important data points that should inform your marketing efforts to him and customers like him. If digital or direct-mail surveys aren’t working, perhaps your sales associates can ask Jim a question or two on his next visit. The ability to create nimble marketing solutions that communicate information across channels is a critical component of closing the “loop” – so to speak – and figuring out how to market more effectively with each engagement.
Consumers want to be treated as individuals. This requires harnessing your data to create contextually relevant and highly personalized content, delivered in appropriate, real-time interactions. By focusing on these first two “Cs” while establishing a process for measuring customer satisfaction, you’ll be well on your way to effectively navigating the new world of modern retail marketing.