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GUEST COMMENT How to avoid the six big mistakes retailers make with data

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Retail is propelling the big data revolution. Big box retailers have IT systems that provide increasingly sophisticated ways of gathering market and customer data. For instance cosmetics retailer Lush uses data insights to change store displays if it notices that a particular item is often purchased alongside another. By embracing user-driven business intelligence, Lush has seen savings of over £1 million in its stock loss. But it’s not just for the big guys. Data analytics can empower retailers of all shapes and sizes, by helping them get to know their business better, spot trends, identify problems and plan for the future. Data also allows retailers to make more reliable decisions in just about every part of their business.

That’s not to say it’s a straightforward process. It’s easy to make simple errors which can lead to a loss of important information and customer trust, not to mention missed opportunities to understand the customer better. A recent UK government sector insights report has said that retailers need to embrace the latest technology trends, such as big data, and have the skills to work with digital systems if they want to succeed.

So what does this look like in practice? We work with over 15,000 retailers around the world, and frequently see six common mistakes from retailers when dealing with their data. Given James Joyce once described mistakes as “the portals of discovery,” I hope you find these errors and the solutions that follow, illuminating, helpful and pragmatic.

1. Ignoring what’s at your fingertips

If you’ve taken the time to collect people’s information through a loyalty scheme for example, make sure you put that data to good use. Having data and not using it is a waste of time and money, and can create distrust with your customers.

By asking your customers for their information, you set an expectation that you’ll engage with them differently, and in better ways, than others. If you don’t meet this expectation then customers will become suspicious about why you asked for their information in the first place. Data should be collected with the chief intention of benefiting the customer – which in turn will benefit your business. For example, high street bakery Greggs does this well through its loyalty scheme, which collects customer data and then provides instant, targeted offers and rewards to shoppers through their mobile phones.

So don’t let all that information sit in some database – use it to engage with your customers.

2. Not using the right tools

Your ability to actually use the data you collect relies, in large part, to the tools you’re working with; so choose wisely. Select data-centric solutions that will not only enable you to gather the insight you need, but also present that information in an organised way, so you can analyse and manage it effectively.

For example, customer data can come into your business through multiple touch-points including emails generated from marketing activity or items browsed on the web. Ensure you have a system that can bring all of these touch-points together so you can manage the data from a central place. Otherwise, you’ll end up with duplicate records and a mine of data that’s time consuming to organise, and causes miscommunication with your customers.

3. Failing to empower your staff

Don’t just train your employees to use your data-centric tools – educate them on how to make the most out of the information so they feel empowered and engaged. This can have a big impact on staff sales and performance.

For example, motivate your team by giving them a deeper look at their sales data and help them figure out when they’re closing sales and how they can improve. You can also train your staff to spot product trends – such as what’s selling, and which items are frequently purchased together. These insights will help them provide richer product descriptions and more thoughtful recommendations to shoppers.

Similarly, empower your staff to take a deeper look at customer data, so they can create a more personal experience for shoppers. If one of your regular customers walks into your shop, your associates should be trained to check out that customer’s purchase history or loyalty status so they can interact with them in the most relevant way.

4. Not having that ‘human touch’

Reporting and analytics can provide great insights, but they’re no match for real human interactions and knowledge.

Don’t rely solely on data and information when interacting with customers. If you know a customer personally, use your own dealings with them as well as information on their purchase history when making product recommendations.

The same goes for customer feedback. Let’s say you’re purchasing new merchandise for next season. As well as looking at your sales and inventory data, you can also consider comments or suggestions from customers. What types of products would they like to see more of? What do they like most about your current selection?

Your analytics software may be able to tell you what’s selling and what’s not, but gathering insights first-hand about how your customers feel about your merchandise can only be done through qualitative data-gathering and communicating with shoppers.

5. Not being safe and ethical with data

Getting customers to trust you with their information – from email addresses and birthdays, to purchase histories – is a significant responsibility, so be careful with it. The last thing your business wants is to come off as untrustworthy, or have to deal with stolen data.

Follow due diligence and always ask permission before collecting customer information. Customers should be able to opt-in and opt-out of your emails, or if you’re tracking their location using an app, they should have the option to allow location-tracking on their phones. This will establish trust with your customers from the outset.

Crucially, keep all systems that store customer information up-to-date. New updates and features mean your software should have the latest security measures. This will reduce their vulnerability to breaches. And, be sure to only use reputable providers or companies that have proven track records and strong privacy policies; particularly if you’ve tasked them with handling payment information and other sensitive customer data.

6. Being selfish with your data

Ultimately, customer information should be used to provide a better service for your customers. This data can help you understand your business and create personal, genuine and compelling experiences for your customers, so they keep coming back.

Bridget Johns, head of customer engagement at RetailNext, the world leader in in-store analytics, has noted that analytics and data insights are primarily about shoppers and their needs and desires. What’s good for them is good for business.

Before implementing new solutions or initiatives, ask yourself if what you’re doing actually benefits your customers, and how it will enhance the experience for them. The benefits will follow from there.

Francesca Nicasio is retail expert at Vend

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