Download White Paper: Improve Sales Force Effectiveness Using Multi-Variable Customer Ranking
For effective sales, companies need to differentiate how they allocate their limited sales resources among existing customers, customer service and new business development (prospects). When ranking Customers and Prospects, the common metric is usually either sales or profits. This paper will show how you can blend multiple desirable sales characteristics including Sales Growth, Close Rate, Payment History, Unit Volume, Repeat Business, along with Sales and Profit, to create an “Overall Performance Factor” for each Customer or Prospect. This Overall Performance Factor can easily be sorted to create an objective ranking of best to lowest performance in which you can prioritize and assign the appropriate Sales resources to meet the company’s objectives.
- Sales Process / Performance Improvement Project
- Customer Ranking – Shortcomings of the 80/20 Rule
- Multi-Measure Approach Needed
- Created a New Customer Ranking System
Supply Velocity was engaged to help our Client, a Property & Casualty Insurance company, evaluate their Sales Process. While they were profitable, this publicly traded company had flat earnings for 3 years.
Part of our analysis led us to evaluate their Independent Sales Force. They sold insurance through independent agencies. These could be sole proprietors who sell one company’s insurance products exclusively or larger multi-agent firms that sell multiple, and even competing lines. At the time of this project they had about 2400 independent insurance agencies. These agencies were their “business-to-business” customers.
Ranking their independent agencies based on Sales (traditional method) quickly showed itself as being an incomplete view. Our client was concerned about multiple measures including Sales Growth, Consumer Retention and Profitability. They needed to do great in all of these measures, plus Sales/Revenue, to meet the earnings growth expectations their investors were demanding.
Supply Velocity created a Multi-Pareto calculation tool to develop a single customer (or independent agency) ranking. This tool used the principles of Pareto Analysis but allowed us to calculate an Overall Performance Indicator based on multiple performance factors.
Multi-Variable Pareto Method
- Overview of Pareto Charts
- Description of Multi-Variable Pareto Calculation
- Force Ranking
- Overall Performance Factor
- Customer Ranking based on Overall Performance Factor
Pareto Charts were developed in the late 1800’s by an Italian Economist, Vilfredo Pareto. He used this analysis to determine that wealth was skewed to a small portion of the population. In his time, 80% of the land in Italy was owned by 20% of the families in Italy. From Vilfredo we derived the Pareto Principal or 80/20 rule. This is commonly used in sales, with 80% of sales generated by only 20% of customers.
Pareto Analysis is a great business tool, but there is more to increasing profit than focusing on just sales, or even just profit. There are leading and lagging indicators of profit growth from the customer base.
The first step was to determine what measures defined great customers (or great independent agencies). To do this we engaged a cross functional team representing Sales Executives, Sales Representatives, Marketing, Finance and Operations.
At the Insurance Company we defined great agencies as having:
- High Sales $
- High Gross Profit %
- Based on Sales $ minus actual payouts to that agents consumer base
- High Consumer Retention
- High Sales Growth
The teams then had to weight these measures so we could apply an “importance-weight” to each of the measures. The total weighting had to equal 100%.
The Insurance Company weighted their measures as follows:
- Sales $ = 30%
- Sales Growth = 30%
- Gross Profit % = 25%
- Consumer Retention = 15%
There was very healthy debate about these decisions. The weighting had significant impact on how the Sales Force spent its time and even what types of customers and/or customer-segments became the focus of its business development activities.
For the Insurance Company, by defining Sales Growth as important a measure as Sales $ they were signaling to their Account Executives that focusing on smaller but growing agencies was just as important as focusing on larger, low growth agencies. As you will see in the data below, many high-sales agencies had flat to declining sales.
Force Ranking mathematically allows us to make all these different measures equal for the overall calculation. This process simply makes the largest number equal to a 10. Then all other customers are proportioned with respect to the largest. This Factor is used in our Overall Performance calculation.
Overall Performance Factor
To calculate the Overall Performance Factor we simply multiply the weighting %for each measure by that measures’ factor.
The last step is to sort the customer list based on the Overall Performance Factor. Then you can make prioritization decisions.
- Green Customers – Get the most focus, time and service
- Yellow Customers – Average customers, how can we move them up
- Red Customers – Can use multiple strategies such as using an inside customer service rep versus field rep to service this customer, or remediate them
- Remediate can include firing this customer or increasing profitability
The results are show below.
Insurance Company – Customer (Independent Agency) Ranking
The next step was to determine what characteristics statistically differentiated the best customers from all others. The team brainstormed all possible ways we could segment customers. There were 72 different possible classifications.
The 3 characteristics that were common (based on statistical testing) amongst the best were:
Did not already sell insurance – These are called “scratch” agents. The best agents for my Client were people that didn’t sell insurance for other companies. There were therefore trained specifically to sell for my Client and were loyal to them.
Had a Business Plan – The old adage “Fail to Plan, Plan to Fail” worked for insurance agencies. The best agencies operated as businesses and had business plans that they followed.
Were in business for 5 – 10 years – We discovered the “sweet” spot for sales revenue, sales growth, retention and profitability were agencies that had 5 – 10 years of experience. This was the high growth time for most agencies.
Instead of treating all customers equally, or rewarding sales agencies with high sales, but no growth, this company differentiated how they allocated sales resources to existing customers and prospects.
Sales strategies were developed based on the Green-Yellow-Red designations. The different color designations required different action plans to achieve improvement. Following the analysis, they recruited insurance agencies that were similar to the high performers, trained them to match the business techniques that were used by the high performers and provided marketing support that was most highly utilized by the high performers.
For the Insurance Company, six months following the implementation of this project, earnings grew by over 26%.