When I was working with a franchise startup, we were seeking a POS system that could grow with us. The winner had multiple reporting capabilities, and the potential to provide an impressive amount of retail sales data.
Our thought was, the more information, the more reporting a franchisee could do to thoroughly understand what was happening in their business.
When we rolled the system out to new franchisees, many were overwhelmed with the 500+ possible reports. They never went into the system to get the data they needed, they just called corporate.
We quickly realized we had to create three reports that would automatically be emailed to the franchisees each Monday at 9am.
But even then, few rarely took notice. They were too deep in the weeds trying to fill shifts and get through the day to work on the business. They felt trapped.
Retail sales data shines a light on the problem, but many choose to ignore it
And that’s still true of many retailers large and small.
Maybe you’re a retailer who looks at your KPIs including average ticket, units per transaction, and average sales per employee per hour.
And these days, big data in retail goes way beyond basic POS reports…
Maybe you’re using Shoppertrak to count who comes into your store, what zones get the most traffic, and how effectively your queue is managed.
Or maybe you’re using IBM to collect, secure, and analyze Big Data generated through mobile, social, and the Internet of Things to see each customer as an individual and in context.
Or maybe you use mystery shops to evaluate, measure, and grade how your crew does against expected behaviors.
Or maybe you’re an apparel store using Alert Technologies’ Smart Fitting Rooms to see how long shoppers had to wait for service when they ask for service, or the average time shoppers spend in the fitting room.
Or maybe you’re one of those NetPromoter retailers using their -100 to 100 scoring system to grade your customers’ overall satisfaction with your company's service.
Here’s the thing…
All that retail sales data is useless
That is... if the data of number of customers per hour are seen just as proof you overwork your employees …
If you just post a mystery shop report in the backroom to show how poorly your employees treated a shopper...
If those reports are just used to measure customer sentiment, they become just vanity metrics.
Reports without action are useless
The amount of data you have coming in must be analyzed for patterns and action steps.
Remember the goal: You collect all these retail data points so you can improve in-store conversions of shoppers into buyers.
4 ways to use big data in retail to grow sales
Collecting big data for retailers only has one purpose - to increase sales and conversion rates, generating more revenue and profit. Let’s look at what your data says about your store.
Here are four ways to use data to improve your sales.
1. Low customer satisfaction scores
Bad star ratings often come from customers who were ignored by associates busy helping other customers. Worse, by associates who are just lazy.
What to do?
Train your employees to always notice someone entering their department. If they are doing anythingthat is not customer-facing, they should stop and greet the customer.
If they are with someone, they should find the next appropriate pause in the conversation, ask the shopper for permission to go greet the new customer, wait for their response, then return afterward.
2. Low conversion rate of shoppers to buyers
Bad conversion rates often stem from overwhelming customers with too many products, too many promotions, or too much disorganized merchandise.
What to do?
Curate merchandise so shoppers don’t have to ask where something is. To encourage add-ons, create intriguing displays with products that feature everything for a project, an activity, or an outfit.
3. Low average check
Too many promotions and discounts will sink your average ticket price. Another culprit is having untrained employees shepherding customers to buy with the employee’s wallet.
What to do?
Notice where promotions are featured. Don’t feature huge savings right up front. When you have a huge discount, put it in the back of the store so customers have to explore your whole store on their way to the price promotion.
You want to attract people with the newest, premium merchandise in the front of your shop where browsers will most be open. The front of your store is where the money is; your full-priced merchandise should be spot-lit to look like the chrome on a ‘57 Chevy.
And remember, retail sales training will help your associates sell value over price for those premium items.
4. Low customer service scores
When there are too many customers and not enough staff, you can bet customer service scores will be horrible.
What to do?
Schedule breaks and meal times to maintain coverage rather than let associates go whenever they want to or together. Pay most attention around mealtimes when employees want to take breaks but when hurried shoppers have a finite amount of time to shop.
The best tool is still just a tool if you never use it
Big data for retailers is just a tool to measure how well a store is doing at selling its merchandise.
Conversion rates are the greatest information you have about how much your employees are either getting shoppers to buy or allowing them to walk.
It’s natural to want to rank employees or stores against each other, but rankings often develop animosity and eventually dismissal.
The goal is always to do better against what you and the crew of your store have done in the past – not measure them against a store that might have a new façade, a new upbeat manager, or a new residential development.
Yes, traffic intelligence like ShopperTrak can help you understand what customers are doing, but you have to take action on the information.
Yes, mystery shopping can tell you a point of time someone received service in your store, but you have to make them a regular feature of your training to discover patterns.
Yes, you can use Smart Fitting Room, but your managers must observe how the employees are using it to help drive sales. Remember try before you buy is the key to converting 70% of apparel shoppers to customers.
Finally, remember your POS system is only able to give you data about those who purchased. It doesn’t tell you about the customers who intended to buy but left.
The goal of every retailer is to accurately measure, understand, and tweak the retail customer experience to convert browsing shoppers into paying premium customers.
With retail sales training, your sales staff will notice every shopper, act on the signs of shopper wavering, reinforce buying decisions and make more sales.
Don’t just notice the data trends.
Take action to improve your conversion rates.