You have probably been hearing a lot about Big Data and Small Data recently. Data mining is big business with all sorts of marketing potential. There is a multitude of uses for Big Data, but in the case of marketing, countless business transactions, social media posts and other sources are often sifted through to identify individuals who represent likely consumers of a product.

Knowing your customers’ habits is key to reaching your customer, so a profile of your likely customer is a critical tool in your marketing toolbox. Big Data looks at the totality of information out there… and it is daunting. Algorithms dig into the data and sort through it all to identify trends to create a customer profile. You get information such as where they live, their income, whether they shop online, viewing habits, etc.

This might seem cold and analytical, but it’s all good information to know, and can help you make some informed marketing decisions. For instance, should you advertise on broadcast television or online media? It represents the science of marketing, but not the craft of marketing or the art of marketing.

That’s where Small Data comes in. It works to understand why a customer buys your product or a competitor’s product. Say your competitor offers their product cheaper and in a variety of colors and the customer ultimately buys from them. What do you need to do to get the sale the next time? Maybe you need to lower your price—or maybe you simply need to offer your product in red. Small Data can help you make that decision.

Here’s a way to look at it: say you are a real estate developer contemplating constructing an apartment building in a certain city. You already have a good idea of what you think a successful building for your budget would look like: maybe 50-70 units, one and two-bedroom units, a mix of luxury and premium build outs, pool, exercise room. Big Data might tell you there are ten recently constructed apartment buildings that match your criteria in the city. Five of them are renting at the rates you need to get to make a profit, but only three of them are fully rented with wait lists. All this is important Big Data you need to know before entering the market, let alone deciding what to build.

Of course, you want your building to fit among the 30 percent that are profitable, fully occupied apartments, so you want to know as much as possible those three competitors. That’s where Small Data comes in.

With Small Data, you may find that the three successful buildings are near public mass transit stops, offer great views or are in walking distance to office centers. That can help you decide where to build. Or, perhaps there is no similar property available so you may choose instead to put a different style of apartment building or select a different city. You may also learn about their renters. How many own cars? That may tell you whether building a parking deck is important. Are the two-bedroom units most often rented by singles? That may suggest they often sublet the extra room, which may be good information to know when designing floor plans. If some of the competition has ground level retail and dining venues, do the tenants patronize them? If so, they may be a draw you want include in your building. If not, you may have more profitable uses for the space.

So you see, the Big Data gives you the overall, big picture—the basic questions you need answered before considering going a step further. Small Data gives you the details you need to know for success.

You must have both when considering entering the China Market. Avela Consulting has the expertise to collect the data needed for informed decisions. Having worked in China for 17 years, we have the cultural wherewithal and networking to leverage the data for maximum success.