Improving Efficiency Through Data Utilization
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Many companies claim, "We have customer data and we use it for sales." However, that alone does not constitute effective data utilization. So, what exactly is data utilization?
What Is Data Utilization?
"Data utilization in sales" literally means conducting sales activities by leveraging collected data. It refers to making judgments or taking actions based on numerical data.
Instead of relying on intuition, sense, or experience as in the past, sales methods are determined by collecting and analyzing data to identify patterns.
While "customer data" is the primary focus, "data related to sales activities," such as sales performance and timing of results, is also crucial.
Let us revisit the three patterns mentioned earlier to see how data utilization changes the outcome.
Pattern 1: Identifying High-Probability Prospects Through Data to Increase Conversion Rates
If information that allows for the assessment of probability is accumulated in customer data, you can follow those patterns to extract high-probability prospects and improve the conversion rate for each visit. For example, if conversion rates differ by industry or company size, you can develop strategies such as focusing your approach on high-conversion segments.
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Pattern 2: Narrowing Down Targets and Prioritizing Based on Data
If customer attributes and current statuses are managed as information, you can narrow down targets and determine priorities based on data. Instead of blindly contacting prospects in no particular order, you can begin contacting them starting with those most likely to convert.
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Pattern 3: Standardizing Sales Methods Through Data for Horizontal Deployment
By visualizing the methods of high-performing sales representatives through data accumulation, you can standardize these practices and permeate them throughout the team, moving away from individual reliance and raising the performance of the entire team. Instead of leaving the timing of visits or the content of talk scripts to individual intuition, these are digitized, accumulated, and shared.
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As shown, promoting data utilization makes it possible to conduct sales activities efficiently.
Although the concept of data utilization has permeated marketing first, the reality is that many companies have yet to implement it in their sales activities.
By seriously engaging in data utilization in your sales activities starting now, you will be able to stay one step ahead of your competitors.
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Beware of Data Utilization Pitfalls
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Many companies introduce DX tools like SFA, collect and digitize data, and input it into the tools, only to encounter the following failures:
- Sales staff are not taught how to use the data correctly
- Data becomes unreliable over time due to missing information or duplication
- Data is not updated appropriately, becoming obsolete and unused
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This is the reason why even with DX promotion, many still feel that "sales have too much waste" or "are not efficient."
To correctly link introduced tools to efficiency, it is important not to stop at just collecting and digitizing data, but to share and practice the following information with all stakeholders:
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- Effectively use collected data for sales activities
- Maintain data quality
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Effectively Use Collected Data for Sales Activities
It is essential to design in advance how to extract (filter) the collected data and how to approach prospects.
Otherwise, there is a possibility of reverting to inefficient sales activities, such as "cold calling all accumulated customer data."
In data utilization, how you segment the data is extremely important.
Decide firmly how to extract information from the vast amount of data. Designing this process also leads to the standardization of sales processes that tend to be individualized.
Maintain Data Quality
Customer information is updated daily along with sales activities. Information such as "what the current status is" is particularly important; if this information is not updated and is missed, correct information will not reach the staff, leading to wasted sales activities.
Furthermore, if data quality declines due to issues like duplication from double entry or missing items, trust in the data will decrease, and the effectiveness of tool implementation will diminish.
Maintaining the quality of customer data is a very important element for sales efficiency.
By keeping these points in mind, you can avoid the failure of "introducing a new tool but failing to utilize it effectively."
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