Why harnessing location data can improve customer experience
Better engagement with customers starts by understanding them better. Many organisations have basic internal information – the types of products they buy and who they are – but they may not know more specific details such as age or interests or family composition. In 2019, we can now turn this anonymous data into known or best-guess information by collecting industry data.
For example, a business might have its customers’ home addresses and emails. A home address can give a business details on where a consumer lives, demographic profile and purchasing personas of those in the surrounding block. Don’t forget – people living in the same neighbourhood are likely similar in other ways, too. That gives us information on what that person might look like according to demographics, but it doesn’t necessarily tell us what they might be interested in.
That’s where the email addresses come into play as they can help with social profiling. You can look at customers’ social media profiles and view how active they are. Remember, on Facebook, LinkedIn or Twitter you are giving up information when you ‘like’ certain posts. We might be able to deduce you are into horse riding or sports or the military, say. We can attach that to your current data in a process called data enrichment.
This all helps businesses better understand what their customers look like, what they’re interested in and where they are. From an audience perspective, that’s gold because it helps you target your advertising and choose whether to put your money into digital, out of home or direct mail.
The next thing to consider is using the information to redefine your bricks and mortar strategy. We know consumers have become much more digital-centric, but they often look for physical reinforcement before they make a final purchasing decision. This means the types of stores we are seeing are changing because of the way organisations are using our data to find out what’s going to resonate in particular areas.
If you think about banks, for example, they are optimising their branches and ATMs based on this kind of insight. New digital banking centres have no staff working in the branch and all transactions are through machines. On the other hand, we’re seeing banking stores pop up in shopping centres with cosy sofas and a friendly environment – matching different styles to the needs of different customers.
Businesses are gathering deep intelligence about their customers to shape the direction of their business and products. This is critical to ensure they stay ahead of their competition. They are being flooded with information coming in: loyalty databases, satisfaction surveys, advertising results and online orders. Pitney Bowes helps simplify the view of this data by bringing all relevant info, enriching it with detailed insights to find out what’s resonating with consumers so organisations can decide which new products to create or define better strategies to engage with customers.
Bricks and mortar businesses are starting to catch up. The internet set the bar high and changed the way customers want to buy. But consumers often feel loyalty towards bricks-and-mortar brands. They need to be pro-active in working out how to get that connection back. They have so much data available but don’t necessarily know how to use it. Many businesses are realising if they work with the information they have available and add third party data, they can create better engagement.
For example, supermarkets used location data to move their online shopping collection areas to more convenient locations. Pick-up used to be quite cumbersome and inconvenient a few years ago but now they are using data to place click and collect locations along better routes. It’s a great example of aligning your bricks and mortar stores with online shopping habits.
The biggest change in recent years for businesses is the granularity of data and the regularity of how often we can obtain it. Previously, we were restricted to census data collected once every five years – and that’s not great for a fast-moving business while everything was in-store or physically based. Now we have access to so many digital interactions and touchpoints providing us with more information including how people move throughout the day. This will continue to shape analytics moving forward and it is already helping new types of businesses spring up – think about Uber, electric scooters or HelloFresh, which are all business models built on detailed analytics insights for services that we didn’t know we needed. This is a trend that will continue and we expect to see many more service-based businesses pop up as the opportunities from a data-based strategy continue to grow.