Big Data for Small Businesses

Big Data today is becoming a marketing tool available not only to large businesses, but also to retail, services and the like. Instead of advertising “for all”, the analysis of specific data allows you to customize your customers' searches more precisely, optimize costs and increase sales.

Big Data is a large unstructured amount of information that is produced and stored in the digital world: where and how many people were located, what actions were carried out, what topics they visited ... Retail, banks, mobile operators, insurance companies have huge amounts of data about each us. All these data can be used to assess consumer behavior and to create analytical reports, build forecasts for business development. The analysis of these data is used in the field of finance, logistics, marketing to predict consumer behavior trends. Your "individual" offers are formed by retailers precisely thanks to the processing of information about previous purchases.

They use technologies such as cloud computing, mobile and social technologies, machine learning, the Internet of things. Business analysts analyze large amounts of data, interpret them for a deeper understanding of the needs of consumers and improve business processes in real time.
Of course, it is too difficult, or even impossible, for ordinary entrepreneurs to do this on their own. However, their services were offered to them by mobile operators. Kyivstar and Vodafon have a variety of information about their customers and do not hide the fact that they use Big Data to create their own services. And recently they offered products based on "big data" for entrepreneurs and other segments of the business.

We are looking for a client

With the help of "big data", knowing the habits and preferences of your client, you can better determine the location for new stores, company branches and the like. After all, the report will show in what places these people are more often. If the maximum passability of a place is important for a business, then Heatmap (“heat map”), a zone where the number of people, judging by the number of smartphones, is the largest, will help him. On the map, you can view the current locations of branches, points of sale or ATMs, as well as add and save new objects. By the way, such reports will be useful in planning promotions. For retailers, such cards are a way of determining the optimal location of new points of sale. During their opening, it will be relevant to do an analysis of potential customers and targeted SMS mailing.

Apt offer

If an entrepreneur plans to expand his business and reach new consumers, Big Data will give him the opportunity to find his target audience and make it a relevant offer. For this, the mobile operator needs the existing base of mobile numbers of today's business customers. The analyst can process the company’s "big data" about their behavior and create a portrait of the consumer. For example, an operator can analyze the trips and movements of subscribers, their age, gender, income, the presence of children and the car, where they are located geographically (home, work zone and weekend zone), which sites, places or locations they visit (here you can add the addresses of competitors, for example), is there a discount to competitors, is it receiving SMS from them, is it calling their numbers. Next, an automatic selection is made from their subscriber base, there are people who are similar in behavior (the so-called Look-alike audience), who are not yet customers of the company.
The next step is to make such people an offer appropriate to their needs through SMS-mailing.
Having a portrait of a client, an entrepreneur can use the mentioned reports in advertising targeting on different communication channels. For e-commerce, the chain can be as follows: consumer segmentation according to certain criteria - analysis of the target segment - search for a segment similar to the target one - communication with potential customers.

Technology Usage Examples

Operators talk about successful cases of using "big data" business. For example, a chain of stores with household goods and cosmetic products wanted to determine the number of potential buyers who live and work within a radius of 3 km from the stores, to determine their portrait for further attraction. After analyzing more than 200 parameters, including the distance from the store, socio-demographic characteristics, the presence of a smartphone, network behavior, we built a model and identified 4 segments for further targeting. Conducted promotional campaigns with individual offers for each segment. Analysis of the results showed a significant increase in conversion. Informing about discounts, sales, discounts or special offers for a specific target audience using Big Data becomes much more effective.
The gas station set out to find new customers. Car owners were found and informed about the opportunity to get a cashback and become participants in the loyalty program. A similar audience was sought and found by an auto parts store.
Among the regular users of the service are cafes that send invitations to middle-income people who are in such cafes and who live nearby. Children's gaming and entertainment centers, fitness clubs that are constantly looking for and attract new visitors. On average, for catering and retail and service enterprises, the conversion of ads built on the basis of Big Data analysis is 10%. Also, this tool is very appropriate for companies engaged in employment both in Ukraine and abroad, because you can find people in specific professions and hobbies quite accurately. In fact, all types of b2c businesses can use Big Data, whose potential customers use the Internet, a smartphone, and social networks.

User Data Security

Operators emphasize that they do not provide third parties with any personal data about their subscribers. They create analytics and reports on generalized personalized information. And the customer can only receive a ready-made report drawn up according to these data.
The data from mobile operators is quite accurate due to the large number of nodes in the computing cluster and horizontal scaling. The analysis of data occurs through a combination of classical business analysis by a person and machine learning, which allows you to find hidden trends, patterns and patterns of consumer behavior.
The entrepreneur is left to put the exact task of finding a client online on the site of the operator or offline manager - and get the results. The life of marketers has also been simplified: “artificial intelligence” is in a hurry to help them in data analysis. About this in the next article.