“We see our customers as invited guests to a party, and we are the hosts. It's our job every day to make every important aspect of the customer experience a little bit better.” - Jeff Bezos, Amazon

A personalised, data-driven approach means retailers can reach out to their customers across a number of platforms, allowing for in-depth customer journeys that combine the ease of online stores with the personalised service of traditional shopping.

According to the ‘Customers 2020’ study by Walker - a customer intelligence consulting firm - customer experience will overtake price and product as the key brand differentiator by the year 2020 ⁽⁴⁾ .

Consumers demand secure payment types and instant product availability, with the option to experience goods or services in person prior to purchasing.

Big data helps retailers build comprehensive views of their customers, and refine stockroom and delivery methods. Those that embrace this are those that will survive.

A multi-channel approach to data means selling to customers through traditional methods as well as online. Big data can help find the right customers for you, by knowing what they’re reading, where they’re looking online and where they’ll discover your brand.

Using big data across a range of channels helps you understand your customers more deeply, and can uncover hidden trends that will open up new opportunities.

Google believes that “the most sophisticated retailers are ensuring their marketing strategies are geared toward enabling customers to convert on any channel.” ⁽⁷⁾

Why? Because they truly understand the value of customers who purchase from them both in-store and online. Even for large online retailers a website combined with direct-response advertising shouldn’t be your only means of reaching shoppers.

According to IBM, “coordinating this multi-channel shopping interaction requires entirely new data competencies for the retailer whose business now depends upon whether it can manage, integrate and understand this vast array of data coming at a non-stop pace.” ⁽⁸⁾

From the earliest days of retail, building beneficial relationships with your customers has required sellers to have an understanding of their needs and wants.

By building bigger, more comprehensive pictures of your customers, including their motivations for buying and their spending habits, you can personalise the customer service you provide.

“Analytics is really the backbone of helping us be quantitative in our understanding of our customers,” says Mike Amend, former vice president of online at Home Depot. ⁽¹⁰⁾

Capture everything

Making your data collection comprehensive means you’ll get a more complete picture of your customers. Mike Dickey, CEO of Cloudmeter, says that “blind spots can lead to missing critical information and a skewed overall picture of a customer’s experience”. ⁽¹¹⁾

But it's not enough to capture this data, you need to use it in ways that highlight not only what your customers are doing, but why. A complete view of your customers can only happen when you integrate data from across the purchasing journey.

Personalised advertising allows retailers to create marketing truly based on demographics, interests, location and even purchase history.

And it allows even the largest organisations to present products and services that are relevant and interesting to each member of their consumer base. It can also allow brands and sellers to create personalised marketplaces, where customers don’t see things they’re never going to buy.

Personalisation starts with a holistic view of the customer and their behaviours and desires. By having a rich image of each consumer, brands can design campaigns that provide customised messaging from the time a search is made, to the moment a delivery arrives or a service is made active.

Retailers that get personalisation right will receive greater ROI from advertising due to targeted efforts, and will be able to market in ways that make customers opt in, not switch off.

Product and service designers are adept at using big data to refine what goes to market. Retailers can use this approach to design ways in which customers experience products and services in person, and how they are delivered.

Retailers can use data to track a customer's journey around stores to design stands and showcases featuring must-see products, and arming their staff with devices that are able to access customer data and stock levels in real time.

Data-driven technology can also allow customers to pay a salesperson from any point in the store, reducing the need for them to deal with their least favourite part of a shopping trip.

Well-managed, compete product data means that inventories are more easily managed, and products will always be available when purchases are made. Data can also be shared with suppliers and delivery drivers to ensure a seamless experience for customers.

Big data can help retailers provide inviting, holistic customer experiences that embrace both the ease of online shopping and the personalised service of traditional “bricks and mortar” stores.

Inaccurate data can mean targeting the wrong consumers and losing track of existing customers. It can lead to products being unavailable when orders and purchases are made, and result in deliveries going missing before they reach their destination.

Clean, accurate data can help create and distribute advertising that’s based on consumers’ tangible needs, not just designed to encourage their desire.

Retailers that embrace data-driven ways of working are those that will take the lead in increasingly competitive markets. However keeping customer databases clean and accurate can be difficult.

If you’re looking to take advantage of data-driven retail, start with the basics and determine whether your database is up to date. Our calculator tool can help you learn why a small investment in data integrity can make a big impact on how well your business connects.