Brands today collect multiple data points across consumer interactions, ranging from key promotional events and social comments to consumer whereabouts and inquiries. One of the key challenges faced by brands and enterprises is to fuse these multiple data streams in real-time and act on them. Overcoming this challenge would redefine how brands interact with their consumers using data today. Here is how: 1. A power shift When brands have a self-serve platform, the ability to collect and fully analyze multiple data sets like demographics, social, location, interest, point-of-sales, and CRM moves to brands and enterprises, giving them control. They now have the power to define the who, what, when, and where of data and get the consumer insights they want. They’re able to conduct their own A/B tests to distinguish the business strategies that work, from the ones that don’t. This also gives them the ability to optimize their decisions without waiting on or working with any data service provider. They can do all the analysis themselves in an affordable, easy and timely manner, allowing them to make decisions much more quickly, and with the most relevant and up-to-date information. 2. Access to fresh data Real-time data is much more useful to brands than historical data because it shows the most recent trends and customer preferences. By keeping up with these ever-changing preferences, brands are able to respond more quickly to shifts in trends and provide customers with exactly what they want. Action on fresh data also results in better conversions, and hence better sales. Brands and enterprises with access to the freshest data definitely have an edge over their competitors. 3. Data transparency When brands have control of their data, everything becomes very transparent including spends. They have access to all of the information coming in, from raw data to established public data sets. They can create, visualize, and analyze any of these data sets, act on them, and see what works for them. When consumer reports can be accessed any time, brands can make faster changes in their marketing strategies and also rethink their business strategies if need be. 4. Digitizing brand data Brands could bring their own data like CRM data and more to the table, mixing it with other data sets in order to gather powerful insights. With multiple data sets and, thus, more relevant information at hand, businesses can make more informed decisions. Currently, brands work with different products and providers for different data sets, and this prevents them from getting a complete consumer picture. With the convergence of the brand’s first-party data and other data sets like consumer location, business strategies can be consolidated. A first-step in this direction is our latest product Allspark (near.co/allspark), that allows brands and enterprises to leverage third-party and proprietary data sets in real-time. The current data sets it consolidates include consumer location, behavior, interest, and demographics, and with certain tweaks, can also fuse CRM data, IOT data, spend data, and social streams. For instance, if Adidas were looking to open a new store in London, knowing where the majority of its consumers are found and their weekend hotspots could help make this decision. Adidas could analyse its audience both in terms of their behaviour and preferences, understand whether their key consumers are professionals, students, or homemakers, track footfall patterns of its own and competitor stores to strategize and also set up its operations in the new location. In addition to this, the insights could also help rethink its product design strategy either to attract new consumers, or boost sales with its target audience from a particular age group. By enabling brands to pick real-time data streams of choice, create a consumer picture, and understand market-wise trends across geographies without relying on data providers, these products are revolutionizing the data industry and changing it in significant, new ways. --- By Anil Mathews, Founder & CEO, Near