How British Land uses data to influence, inform and deliver

Something big is coming. Some, in other industries, would perhaps argue it has already come. The way we think about, view, analyse and interpret the world is changing. Increasingly, decisions are being guided, if not made, by data. Big data. The retail environment is awash with data: traditional in-stores sales transaction data, sensor data, mobile, social media, e-commerce and all the adjacent, open-source information that exists around people and people’s habits. You name it, somewhere there is probably a data set on it. But just collecting lots of data is useless if you don’t know what to do with it. And having lots of data and knowing what to do with it is no good if you don’t actually use it. And use it in a way that transforms, influences and enhances your business. In retail, there is one landlord that has committed fully to the power of data in guiding and making business decisions. British Land first started looking at the role of data and the information that could be provided by its collection and analysis in 2012. Back then, it was already becoming clear that online shopping and the growth of omni-channel was going to change the face of retail. “We realised then that there was an opportunity to use data for analysis and insight in our decision-making more fully,” says head of retail business development Ben Dimson. BL’s data collection started relatively simply, or traditionally at least. Surveys were conducted at shopping centres up and down the country. BL spoke to its customers (shoppers) at every site at least once or twice a year. “We were having 40,000 conversations a year with our shoppers to understand who they were, what they wanted, how they act and behave and what they might want in the future,” says Dimson. He says the project has evolved and grown since then, particularly over the past 12 to 18 months, with a much richer combination of data being collected and a much deeper and more valuable level of insight being delivered as a result. Intelligent data BL now has a dedicated insights team that operates across the whole business to develop the REIT’s understanding of who its customers are, how they behave and what their preferences are. The team collects and analyses operational data such as footfall, dwell times and sales, geographic and demographic data on local catchments, including online data from around 3m individuals and 12m visits to its retail centre websites each year. Data from sensors provides yet another source of information (Dimson says they are currently looking at 80m rows of number plate data from sensors at its centres), as do those traditional customer surveys. The information collected is used in a variety of ways. It used to improve parking and public realm, to manage tenant mix, mitigate risk and reveal opportunities. “If you think about our business and the different functions we have got around investment and divestment of assets, developing or refurbishing assets, asset management in the broader sense in terms of the services and facilities we provide, and in the narrower sense in terms of leasing and line-up, we have thought about all the those different decision points in the business and how we might use data to support those decisions,” says Dimson. “You have to have the best space, but taking a more systematic approach to understanding what is going to drive success and where we as a business can add value is definitely helping us be clear on our investment decisions, in terms of the assets that we ought to keep spending more money on to improve or extend and which ones may be aren’t such a good long-term fit.” But Dimson says utilising data in decision-making doesn’t mean taking the human element out of any part of the process. “This isn’t in any way a move away from years of experience and business relationships. It is to supplement and add an extra anchor point. An extra, objective, a way in which we can measure things and challenge the status quo, and hopefully by combining these separate skill sets and approaches, come to better outcomes,” he says. Targeted research So how is it working in practice? Are those better outcomes being delivered? Ben Grose, head of national leasing, can deliver some live examples. Take Hotel Chocolat leasing a store at BL’s Teeside shopping park in Stockton-on-Tees, Country Durham. Its first in a non-traditional location. “There is no doubt the data we were able to provide – whether it was a gap in their portfolio in that particular region or the demographics and how well they were aligned to their customer – was helpful in helping them reach a decision,” says Grose. Superdry taking a store at Glasgow Fort is another example. Grose says the REIT had been talking to the retailer for several years about taking space at the Scottish shopping park. While it was not just the data that tipped Superdry over the line (environmental improvements to the scheme helped too), the insight BL could provide certainly influenced the decision. “Data is either helping open conversations on things people wouldn’t consider or helping tip them over the edge when they are unsure,” adds Dimson. “It is never the sole reason someone does something.” He says that having access to and understanding data can be really useful in helping retailers understand what cannibalisation really means. Historically, a retailer’s method to decide whether one store will cannibalise another has largely been based on gut feeling and drive times. That is OK, but data can make it so much better. “By really understanding, in a detailed way, across multiple sites, the different spread of customers, how different catchments work, demographies, how shoppers behave at particular sites, etc you can get under the skin of modelling what that cannibalisation might be,” says Dimson. “We have quite successfully challenged some preconceptions because even though two sites might be geographically close, they might be serving quite different catchments.” Dimson says using its various sources of data, from census information to Wi-Fi data, it can probe and test how a catchment looks and feels around individual sites. BL can identify that a certain shopper might live in a certain area, it can know what habits they have, how often they come to a centre, how often they buy something at that centre, how long they visit for, what shops they visit, what they buy, how much they spend, and so on. In one recent discussion with an unnamed fashion retailer, by using almost 250,000 of its survey results, BL was able to build a complete profile of the retailer’s customer. The profile resonated so much with the retailer’s own view of its customer that it enabled BL to start talking about all the other places in its portfolio that were a good match to that profile. But it is not all rosy in the world of retail data analytics. While BL is collecting data and sharing its insights with its customers, a two-way share is something of an exception not the norm. “In a tough and challenging environment, the key now is collaboration,” says Grose. “There needs to be a more collaborative approach between landlords and tenants. We have a lot to help retailers with, which could be as granular as looking at product mix within a particular store. We are gradually seeing more openness from retailers but there is still mistrust and those barriers of mistrust need to be broken down.” Wholesale change And the market needs to start breaking down those barriers soon as the role of data in all sorts of decision-making is only going to grow. “Data is not a real estate thing,” says Dimson. “This is going industry after industry making wholesale changes. It is about how you use information to make decisions and it is hard to see it going backwards. “There are some watch-outs along the way. You do need to look at the loyalty schemes and understand why some of those have been more successful than others. You can drown in the data because the volumes just get bigger and bigger. “You need to stay front and centre of what the business problem or decision you are trying to solve is and how data can help you do that, rather than can carried away in the technology or data for data’s sake. But, as long as you stay focussed and are working collaboratively, I can only see it becoming more relevant over time.” To send feedback, e-mail Samantha.McClary@egi.co.uk or tweet @Samanthamcclary or @estatesgazette