3 steps to monetize the sales team
Traditionally, the calculation of a customer’s sales potential is based on the average turnover with this customer (resulting from the analysis of historical sales) to which a percentage can be added according to the evolution of the market itself. However, this methodology causes a bias that we imprint on our own activity and that prevents us from accurately assessing the true potential of each client.
In order to gain a broader view of customers, a very methodical analysis of company data and third-party data is needed to enrich them.
Step 1: Have a clean and enriched database with all data of interest to our customers
Typically, the internal data sources that help us estimate how much we can achieve in sales on each customer come from the CRM itself and generally are:
- Sales from previous years and accumulated to date (probably also by product lines).
- Commercial activities carried out in each client:
– Number of visits per sales cycle/year
– Support Promotions/material to be delivered
– Specific training
– Trade Marketing activities
- Customer characteristics:
– Customer Category
– Type of trade (eg pharmacy, para-pharmacy, perfumery, supermarket, hairdresser, HORECA, etc.)
As external data sources that provide great value for the knowledge of the customer portfolio, we can mention:
Socio-demographic databases that describe different aspects of people who live or move around the point of sale, such as:
- Social class, socioeconomic status, housing prices, schooling, work activity, …
- Grouped by age, sex, family type, …
- Habits of purchase and consumption, etc.
Real estate data near your location:
- Number of buildings
- Height of buildings
- Buildings antiquity
- Area by type of property (commercial, leisure, residential, etc.)
- State of conservation of real estate
Data that contains trade location information:
- The proximity to health centers, hospitals, universities, etc.
- Proximity to the coast or ski resorts
- Situation in shopping centers, etc.
- Business Databases
- Sales by category
- Number of Employees
- Number of boxes
- Trade Zone
- Competitive data
With all these databases, the first problem to be solved will be to obtain the unique vision of each client or, in other words, to unite the information coming from the different sources.
In the case of sociodemographic databases these will be linked from the client’s location (geographical coordinates). This will require performing an earlier geocoding process from your address.
To get information from external databases you must join the customer information that we have internally. This can be done through key data such as NIF, which are not always available. When we do not have this data to make the union, it is necessary to resort to processes of data cleaning to try to cross by name, telephone, address, etc. as well as algorithms that find similarities between the fields of the different databases. Usually this union can not be done directly and has several iterations, and a manual treatment may be necessary.
We have at this stage a clean and enriched database with which to work.
OBJECTIVE 1 COMPLETED !
Step 2: Define optimal sales territories and a smart strategy.
Once the analysis of internal and external data has been completed, we obtain the following results:
1. Total potential sales of a product line or product. Statistical techniques are often used to calculate this. With these techniques we try to predict the current sales from the information collected in our dataset. This results in one or more formulas, where each variable has a weight. By applying the formula to each customer, we have a potential sales value in euros.
2. Segment customers. From potential sales, customers must be classified and associated with a category. There are two types of targeting: strategic and tactical.
Strategic Segmentation implies the allocation of a unique representative label to each generated customer group, and provides a descriptive overview of each of the segments. For example, Type A customers (those with a high potential for sales and near a hospital), type B customers (those who have an average sales potential and are located in urban areas), type C customers (those that have an average sales potential and are in rural areas), etc.
– Customer recovery
– Cross selling or cross selling
– Capture of new customers: The type of campaign applicable to each segment of customers is conditioned by their situation in a value-fidelity matrix as shown in the following figure:
Having this information is necessary to translate it into an acceptable strategy for the sales team. We must consider the size of the sales team, the available working hours, the number of customers per segment, the estimated length of business visits, etc …
This will result in a distribution of such customers into geographically ideal sales territories, number of customers, turnover and sales potential.
Next, a visitor frequency by customer type is defined which must take into account all previous parameters (for example, type A clients will visit four times a month, type B twice and type C at least one). In a tuning phase of this optimization, these frequencies should also be weighted according to the workload of each territory.
This will define optimal sales territories and an intelligent strategy of visits to customers based on the capacity of the sales force.
We are now well acquainted with the customer base and sales potential
OBJECTIVE 1 COMPLETED !
Step 3: Put the business team more time with customers and less time on the road or lost in Excel files.
Lastly, it is necessary to allow the sales force to achieve the strategic objectives by offering tools to enable it to focus on what is essential: the sale.
Selling is a process where for many markets it is not possible to replace human interaction and it is precisely here that forces must focus, leaving the rest to what technology can replace and can do so much more effectively and efficiently than the human.
At this point, a route optimization / scheduling tool can be made available to the team. This solution should take into account the greatest possible reduction of expenses, predefined visiting frequencies per customer segment, as well as the unforeseen events of the commercial activity (trainings, courses, trips, meetings with clients or staff, cancellations, etc.). Some tools also allow the reporting of all the actions performed at each visit, the follow-up of product orders, GPS tracking, representation cost control, etc.
Each goal described may have a different meaning in its own right, but it is the sum of them all that will really make a difference to a before and after relationship with customers and sales growth.
In any case, it is necessary that the whole process of optimization involves a great internal transformation that is not free of difficulties. Therefore, the company must take this as a challenge and see innovation as a strategic axis to increase sales.
OBJECTIVE 3 COMPLETED !
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