lone woman walking
Decisions from big data insights can make the customer journey useful, relevant and convenient. PHOTO: Mike Wilson

The retail customer experience has evolved from primarily focusing on the end game the transaction — where consumers would be rewarded at the point of purchase to a holistic, data-driven process that uses insights to give people what they want during all phases of the journey.

No matter how large or small a retailer is data must be the driving force used to improve products and services, and both the in-store and online experience.

It’s certainly challenging to pare down relevant information from masses of data and then make it actionable. However, once uncovered and analyzed, decisions from big data insights can make the customer journey useful, relevant and convenient — all factors that contribute to loyalty and ultimately, increased sales.  

Who Are Your Customers?

To begin thinking about the customer experience in its entirety, retailers must have a clear understanding of who their most valuable audiences are, why those customers behave in the way they do, what they want those customers to gain from their brand and most importantly, what the customers themselves want to gain.

Only by asking the right questions can retailers identify where to begin navigating the overwhelming wealth of information that data systems hold.

Ask questions such as:

  • How do customers best respond to your brand communications? What have been your most successful promotions?
  • Do customers engage with your brand on social media and if so, how and when? What do they complain about the most?

By using both internal data and accessing publicly available external sources such as social media, online browsing and even the Internet of Things, retailers can obtain that 360-degree view necessary to provide an optimized, inclusive customer experience.

Where Are Your Customers?

Once the “who, what and why” are established, the next step is “where” — as in where to look for those insights. Internally, it can be as simple as investigating how customers are behaving on a retailer’s website or mobile app.

Analyze insights such as what products or services they look at the most, how many times they visit before they purchase, through what means they’re purchasing (i.e. in-store, online, mobile, or a combination).

It’s also important to identify if they used loyalty rewards to make their purchase and if they post about their purchase and/or the shopping experience on social media. Slice and dice these findings in as many ways as possible to pinpoint patterns based on factors like age and location.

All of these conclusions are pieces of the data puzzle that define both the individualized and the mass-appeal shopping experience.

What Do Your Customers Want?

US consumers want a shopping experience that’s customized to their wants and needs. To accommodate this overarching sentiment, use captured data to make informed decisions that will foster loyalty and ultimately, revenue.

Best practices include:

  1. Communicate relevantly: Communication is strongly linked to driving the passion and intimacy that is essential for the strongest relationships, as evident by 53 percent of US consumers who would buy more if brands communicated with them better. Customers will respond to communications if they are tailored to the products and services they care about, so long as it’s via their preferred method of contact. 
  2. Reward strategically: Today’s consumers like personalized rewards that “surprise and delight” them. As part of a data-driven strategy, encourage customers to share their preferences and then use that information to provide them with the tailored in-store, online and mobile experiences they desire.
  3. Recognize your brand advocates: Never underestimate the value of word of mouth. The more loyal customers feel, the more willing they are to recommend a brand to others, in turn helping retailers to acquire new customers. Figure out how these customers are promoting your brand, whether it’s via social media, email referrals or otherwise. Track these referrals and reward those customers for their loyalty.
  4. Value the valuable: Big Data allows retailers to predict customer demand, but they still have a ways to go when it comes to valuing the most loyal customers over those who appear just once in a blue moon. Building customer profile data in such a way that allows retailers to tier their customers is not as complex as it sounds and will help to drive loyalty in the long term. 

Many brands today are taking full advantage of big data, using it to accurately predict customers’ wants before they even realize what they are looking for themselves.

Brands of all sizes should be using data-driven insights to foster customer loyalty. The key is answering these “who, why, what, where and how” questions so that retailers can strategically and efficiently pilot through the big data waters to make more strategic decisions and take a customer first approach.