Five reasons why in-store retail analytics is important for your business

Stores are increasingly using in-store retail analytics to aid smarter business decisions.

Five reasons why in-store retail analytics is important for your business | StoreTech

More customers, to sell more, and repeat

Retail analytics

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Every retail business wants to have more customers, sell more to each customer and have them come back to shop again the next time they need those items. To do this, a store needs to offer them the products they want at the right prices. But they also need to offer the right customer experience. Managing all these elements can be tricky and this is why stores are increasingly using in-store retail analytics. Here are 5 reasons why this software is important for your business.

Accessing and understanding data

The ultimate desire for a business owner or manager is to better understand their customer to maximise profits and engender customer loyalty. While there are ways to do this without the use of in-store analytics, they are unreliable and random.

However, with the use of quality in-store analytic software, a business can gain the kind of insight that was previously limited to online stores. This can range from footfall counter information through to where in the store customers visit and even information about how many people look in the store window and don’t come into the shop.

The system uses a combination of Wi-Fi hotspot data and information from CCTV images to help build a picture of every customer that is anonymous and doesn’t infringe data protection regulations but offers businesses a previously unavailable level of insight into what their customers do.

Understand customer behaviour

By gathering this data and allowing stores to access it in an organised and practical way, the manager or store owner can learn more about their customer’s behaviour and how this affects their shopping habits.

One example was the use of mood analytics. This uses CCTV camera images to monitor the facial expressions of a person. One woman was in the store for 45 minutes and had spent half an hour in the shoe aisle. She looked tired and was probably hungry as it was approaching lunch time. To help her, the store could text her a short-term money off coupon for shoes that might spur her into making a decision. Or a voucher for the restaurant to prompt her to grab something to eat and feel better!

While this might seem intrusive, customers are already expecting stores to know what they are thinking. When we are online, every click or cursor movement is recorded and shops will send vouchers, codes, adverts or other material based on that data. By using in-store analytics, we are simply offering this same use of analytics as done online.

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Better use of staff resources

Staff management has always been a process that relied heavily on the experience and gut feeling of the person compiling the roster. When do you need maximum staff and when would half the staff be suitable? Using in-store analytics means that this doesn’t need to be a chance experiment but can be based on hard data.

The software collects customer numbers, patterns and also factors in things such as holidays and special events. This then allows managers insight into when the most customers are routinely in store as well as special factors that might affect these numbers. This makes create rosters a data-driven experience.

It also allows the recording of staff data to solve problems such as people being allocated incorrect hours or shift patterns they cannot accept. This results in happier, more productive staff.

Offering a better customer experience

According to Microsoft, 73% of customers prefer to do their business with brands that offer a personalised buying experience. The online world is already focusing heavily on ‘user experience’ and this is something that the offline world can embrace through the use of in-store analytics.

The growth of IoT technologies such as smart shelves is one simple example. Nothing frustrates customers more than arriving to find an item is out of stock or having to chase down a member of staff to refill an emptied shelf. New smart shelves will let stock managers know when an item is sold out and ensure refills can be done in a timely manner. This means customers will always find what they are looking for.

The evolution of loyalty programs can also help offer a better customer experience and build customer loyalty. Loyalty schemes can help to build that loyalty and ensure customers keep returning to the store. The use of text alerts to give them specialist coupons or vouchers is just one example. Creating a more personalised experience will ensure customers return to the store time after time.

Making best use of visual merchandising

In retail stores, the use of visual merchandising is key. You need to attract the attention of customers and there are lots of visual merchandising tips available to help you make the best of your retail space. But how do you know what works and what doesn’t?

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This is another area where in-store analytics can offer real-time data to help stores see how their visual merchandising is working. Say you add a new product range with its own point of sale stand to attract the attention of customers. With in-store analytics, you can see if customers are stopping to look at it or are walking past. You can see how many of them even walk past it in the first place – this could lead to a relocating of the stand to increase exposure.

Stores can try different visuals and see what has the desired effect on the store. Much like A/B testing in advertising, the use of different themed stands can help isolate which works best and where it is the most noticeable around the store. All of this increases the impact of the visuals.

Often retailers run into the problem of price matching and trying to offer something at a lower price than their competitors. But one of the big branding ideas of recent times is about offering customers a better experience and better value, not just a cheaper price. This might be in the form of limited time offers, exclusive offline products or through loyalty schemes that reward their return visits.

These are just five examples of how in-store analytics can help businesses. By offering a more modern style of shop experience, offline stores can compete more with the online world and can quickly alter strategies if it is clear that something isn’t working. And the more accurate use of staff resources offers a better customer experience, resulting in customer loyalty and happier staff.


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