How to bring business to the end customer?

IBM highlights how predictive analytics solutions-focused on statistical methodology and data mining-can help companies improve management with their customers, both when designing more precise strategies for portfolio expansion, and to prevent and avoid dropouts through the development of specific actions.

The greater competitiveness of the markets is reducing the effectiveness of marketing campaigns and attracting clients conceived in the traditional way. It is necessary to develop specific actions that ensure recruitment and loyalty, for which it is vital to have extensive information on the characteristics, needs and evolution of each client that allow to offer an attractive solution tailored to their requirements. In this sense, recent innovations in the statistical software sector can help bring the business to the end customer in accordance with the follow-up of these five fields of action:

1. Segment your customers . Both in the projects that are already included in the company’s portfolio and, especially, in the projects for acquiring new clients, the marketing actions must be preceded by an adequate segmentation of the whole. The common strategy is to group them by demographic profiles, attitudes or purchasing patterns, but using the new tools of statistics and data mining can still achieve greater accuracy including text data, web or survey results that provide a more detailed view of each segment.

2. Identify the most attractive customers . Statistical methods can be one of the main aids in providing information that goes far beyond what can be obtained through conventional channels and define a profile of customers more susceptible to offers. As an added value, data mining tools can discover very useful subtle patterns and relationships, even if they are hidden among large amounts of data.

3. Determine the approach methods . Massive and unspecific approach strategies have little success in an increasingly specialized market and with increasing competition from supplier companies. Therefore, it is necessary to know the company exhaustively before determining the most appropriate processes to reach it, in a strategy that also minimizes costs and maximizes the impact on customer acquisition. The statistical management tools are a crucial aid here, because the information they provide helps to synchronize the strategies with the particular segments of the organization’s clients.

4. Do not neglect the retention . The abandonment of a company by a client can occur suddenly and come completely by surprise. But on almost all occasions, this has been preceded by signs and indications that would have allowed to predict it in advance, and take measures to avoid it. Predictive analysis facilitates the proactive identification of clients at risk of leaving the business, and encourages the development of relevant offers that allow them to be maintained before they take the decisive step.

5. Optimize your campaigns . A company that organizes several marketing campaigns every month will find it difficult to reach their potential customers at the most opportune time and in the most appropriate manner. The solution lies in predictive applications specifically aimed at optimizing campaigns, which employ statistical analysis and data mining to make the most of available information and focus them precisely through the appropriate channels.

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