How can you master the flow of information generated by Big Data to turn it into a real strategic asset for the sales function? Digital transformation continuously increases the volume of data a company can collect. Is this, however, synonymous with efficiency in sales management? According to an EY study – Big Data: Where do French companies stand? – 45% of companies collect data without it being structured afterwards.
The era of Big Data has highlighted the value of information as a driver of influence, customer satisfaction, and anticipation. However, how can you avoid drowning in information overload? Is it always possible to leverage the data you collect? In this article, we explain the key steps to make SMART Data the new strategic asset for your business relationships.
“Operation Downsizing”: Streamline data collection
Your first challenge will be to transform how you collect your data. There are many powerful tools capable of providing your sales team with maximum customer data. However, multiplying sources and variables will not increase their ability to process and leverage qualified information. On average, salespeople spend over 30% of their time searching for missing data in your CRM. The urgency then lies in the consolidation of existing data. To do this:
- Define with your sales team the most useful sources and types of information for them. Then, focus your attention on the most relevant information sources to obtain and update it long-term.
- Then, create filters to process incoming information “funnel-style.” Consolidate the information until it becomes “valid” before making it available for consultation. For example, if a salesperson can meet 20 new prospects per month, opt for a filtering system that allows these 20 new, fully detailed leads to appear for them. Free them from the other 80 that you have simply identified but not sufficiently detailed.
Out with “Data,” in with “Customer Information”
Then, define indicators that will allow you to automate immediate data processing. The idea is not to overload your database with raw data, but to offer only information (complete, structured, analyzed, and interpreted data). Find the keys to build high-value information. (Customer behavior, high-potential opportunity leads, arrival of a new competitive offer…). The digital solutions available in Data Science offerings are very diverse: scoring, text mining, data mining, etc. They will then allow you to best leverage raw data in an automated way. Then, ensure that the information produced is formulated more effectively. Don’t hesitate to visualize your data. New data visualization solutions in real-time can save you valuable analysis time.
Connect information to your strategic options
Furthermore, the value of SMART Data also lies in the immediate transformation of data into actions. Once you have built and validated your information, identify the “signals” that will allow you to better anticipate certain customer behaviors. You can then immediately connect them to a pre-prepared plan. This technique will allow your sales team to know what to do directly in case of an “alert.” For example, you have identified in your market that a buyer is ready to make their first strategic decisions between the 4th and 5th month after starting their position (information). As soon as a new recruitment is announced (signal), trigger the action plan to be implemented. You will maximize your chances of developing this new lead in due course.
Managing in the SMART Data Era: Extracting the Right Objectives
Finally, it is sometimes difficult to explain predictions based on the data you analyze. Most of your analysis tools are based on phenomena, which can themselves depend on other exogenous variables. Therefore, the task is not easy when it comes to transforming your predictions into objectives. For example, it can be difficult to explain to your sales team that they will maximize their chances of securing a client visit if they make a call between weeks 37 and 42. This also requires a lot of adaptation. Therefore, make sure to gradually break down objectives, focusing on the most reliable information.
As you can see, intelligently leveraging customer information requires a lot of creativity, time, and strategic perspective. The sooner you transition from a “Big Data” approach to a “Smart Data” approach, the more time and efficiency you will gain in the long run.