By Lindsay Sykes
Retailers have access to more data than ever before, but they need ways to turn that data into actionable insights for their customer experience (CX) programs.
A 2017 Forrester report shared that nearly three out of five data and analytics decision makers in the retail industry classify big data and analytics as a high/critical priority for their organization. As a result, these retailers are looking for solutions that deliver visibility and insights into real-time consumer behavior for the entire retail organization.
While traditional analytics can tell you what customers like now, predictive analytics can inform you what a shopper will want next.
Predictive analytics is a form of advanced analytics that can be used to make predictions about future customer behaviors using multiple techniques such as data mining, statistics, modeling, machine learning and artificial intelligence.
Data is analyzed and can be used to track purchase history and other customer data to make recommendations about relevant products based on customer shopping patterns.
Predictive analytics offers a proven way for retailers to use all the CX-related data they’re collecting to support better achieving KPI targets for their stores. Whether it’s information on pricing, inventory management, or revenue forecasting, predictive techniques enable retailers to unlock the power of this data and understand how to serve their customers best.
Here are four ways to improve CX in your retail stores using predictive analytics:
Personalization is becoming increasingly more popular and is now expected by customers. It’s a way to show your audience that you know and understand who they are and what they want.
Creating personalized customer experiences builds brand loyalty and is a key to retaining customers who spend more, share their experiences, and return to your brand time and time again. A study by RJ Metrics found that the top 1% of your customers are worth 18x more than your average customer.
There is an opportunity for brick and mortar retailers to create personalized in-store experiences that exceed anything customers can get online. An Accenture study found that 75% of consumers are more likely to buy from retailers who offer personalized experiences.
By using predictive analytics, the shopping experience can be personalized down to the smallest detail. This requires going beyond the basics of customer preferences by anticipating customer needs to incentivize purchases.
For example, Target looked at historical buying data for all the women who had signed up for Target baby registries in the past and noticed correlations between certain pregnancy products and how far along a woman was in their pregnancy. With this data, Target was able to assign a “pregnancy prediction” score so they could send pregnancy-related coupons timed to very specific stages of a woman’s pregnancy.
Enhance Inventory Management
Inventory management continues to be one of the biggest challenges for retailers, and every customer knows how frustrating it can be to look for a specific item and for the store not to have it. This negatively impacts CX as customers come to the store for the hands-on experience and expect immediate gratification.
Predictive analytics can use past sales and shopper demographic data to determine which stores should carry what inventory, in what size and style.
Inventory management needs can vary depending on physical location, and predictive analytics can ensure that in each location, you’re aligned with the needs of the shoppers in that area. The goal is to have the best inventory for that specific group of customers to help enhance CX.
For example, big-box retailer Kohl’s uses predictive analytics to assist with merchandising allocation, including macroeconomic and social data. This approach helps them to ensure the right merchandise is in each store and encourages faster turnover of their inventory.
Having a blanket approach to inventory replenishment can end up creating both overstocking and understocking issues depending on the needs of each location. Using predictive data helps prevent each store from holding inventory that will be hard to sell, thereby reducing inventory costs and adding to the bottom line.
Measure and Manage KPIs
The ultimate goal of CX for retailers is to improve KPIs, such as average sales per transaction, average units per transaction, store traffic, and net profit margin.
Predictive analytics creates a clear link between your CX measurement program scores, such as customer surveys, mystery shopping, and business results. With predictive analytics, you can identify trending problems and pinpoint areas for improvement that have the biggest impact on your KPIs.
Having defined KPIs that your staff clearly understand, allows you to make the connection between the actions your staff take and how that supports the broader goals of the company.
In a case where you need to provide your staff with some performance feedback, being able to show them how certain actions or behaviors (like upselling at the register) directly impact a specific KPI (like average transaction size), makes the feedback more relevant and tangible. Creating that link for employees makes them more apt to follow-through and reinforces the value of their contributions.
Offer Event-Based Promotions
Throughout the year, numerous events occur that can be used to trigger promotions in retail locations. These events, such as weather or special events, can be used to improve CX with timely, relevant offers to your customers.
Using predictive analytics, you can identify these events and then offer event-based promotions at the regional or individual store level to create a unique and memorable customer experience. Specific criteria such as low traffic could trigger events during a specific time of year, and actions indicated around those slower times to offer promotion or incentives to help to bring customers to your location.
With predictive analytics, there could be specific triggers for weather events, such as a large snowfall. With that trigger, a regional “blizzard” special could be put in place for items relevant to a winter storm, such as shovels, snowshoes, or salt. The same idea can be applied to local events, such as a summer music festival, sporting events, or community celebrations.
An example of this is the partnership between Pantene, Walgreens, and the Weather Channel. Using data collected by the Weather Channel, Pantene and Walgreens were able to anticipate when the humidity in the air would be at its highest, prompting women to seek out a product at their local drugstore to prevent frizz and flyaway hair.
This was branded as a “haircast” and lead to a 10% increase in sales of Pantene at Walgreens for July and August, along with a 4% sales lift across the entire hair care category at Walgreens. It also spurred the creation of social media discussions under the #haircast tag.
A customer of Intouch Insight, a top retailer of Motorcycle parts and apparel, explained how their customer experience is affected by seasonality:
“When fewer customers are coming in the stores the energy of the team is lower, and they’re more apt to do operational tasks. As floor traffic goes up, the team is more active, and they’re managing the customer flow. They’re more on their game, so they get better results overall, like better customer engagement, closing more sales, offering add-ons.”
Having the power to predict their peak times versus down times enables them to offer incentives for employees to keep them performing at a higher level and ensure they continue to make an effort during off-peak times.
The use of predictive analytics to engage and relate with your customers is a winning strategy when it comes to your CX. Retailers that leverage predictive analytics are better able to anticipate and understand their customers’ needs, which helps to enhance CX and positively impacts the bottom line.
Lindsay Sykes is the Director of Marketing at Intouch Insight. To get more actionable strategies on how to improve CX in retail stores, sign up now to get your free copy of the Customer Experience Playbook: Designing a Winning Approach Whitepaper