Building an effective sales funnel

Aim:

To maximize the number of contracts with potential clients of the bank among small and medium-sized businesses (SMB).

Context:

One of the five largest Russian banks applied for a solution based on data analysis and geoanalytics, which would increase the number of transactions with companies from the small and medium-sized business segment without additional financial and time costs. Prior to the implementation of the solution, the process of converting cooperation offers into contracts was carried out according to a long-established unoptimized scheme, and the cost of expanding the staff did not lead to a significant increase in the number of customers.

Solution

The Marketing Logic team analyzed the bank's product and client portfolios and identified criteria for each of the available areas, based on which a particular company becomes a potential client. These criteria included the geography, industry, type of activity, and revenue of the organization. After a detailed digital analysis of the client's profile, we combined all the available databases with information about small and medium-sized enterprises in the region and enriched them with additional data: contacts of representatives, PIN, working hours, information about clients and contractors, etc.

Based on this information, we formed our own sample for each of the bank's products, displayed this information on a map, which was then divided into segments. In this way, we grouped companies located close to each other that were offered the same product. The structured data was transferred to the bank's call center, where each employee worked on his own segment. He, in turn, passed them on to a colleague from the department for meetings on the ground and the conclusion of contracts. For each of them, using MLead tools, we have drawn up an individual route - following it, the employee conducted the maximum number of negotiations in the minimum amount of time.

The process of improving the efficiency of the sales funnel and conversion took place in three stages. With the help of a retrospective analysis of customer data and product line, we immediately excluded companies that would definitely not have signed a contract, thereby saving the bank's resources. At the second stage, we redistributed the load on the call center employees so that they could make the maximum number of effective calls in the shortest possible time, since they did not need to adapt to the specifics of each company – the list was compiled taking into account all the factors that simplify communication, and taking into account the specialization of the bank's sales department employees. At the last stage, we built up logistics, which allowed us to increase the number of meetings and, as a result, transactions.

Result

As a result of using the geoanalytic approach, big data analysis and machine learning, the bank's team and Marketing Logic significantly increased the effectiveness of customer attraction – with full control of the sales funnel, the conversion to contracts increased by 56%