The aim of this blog post is to leave you with a concrete approach to using your time and resources well in order to reach potential customers.
We have developed a method with 9 levels to help you get started easily with data-driven prospecting and grow steadily more mature as a salesperson or sales department. Here we describe the first 5 levels.
Framework
These points in the framework describe what we actually want to achieve:
- Identify and register
- Enrich with data
- Analyze and assess risk
- Monitor and alert
These 4 areas can be made more or less complex. The method we use both internally and together with our customers is described here through the 9 levels of maturity in sales organizations. We have templates and practical aids available for most of the levels.
Identify and register
Level 1
You have several customers, each with a unique identifier, in one system.
Yes, it is true that this is not a given for everyone. We know that many organizations have customers spread across several different systems and may never have brought that information together.
There are probably duplicates as well (we will cover that in another blog post about data cleansing) and other issues that make it hard to get a complete picture of what the existing customer base actually looks like. Unless the data in this foundation is clean and uses the same identifier, you will not be able to move on to the next levels without running into problems later. In B2B, the most common identifier is the organization number. If that is correct, you have a good starting point.
Enrich with data
Level 2
You have the right information about your drivers of growth.
You have worked out which characteristics make a customer worth spending time on. Your pricing model is based on this, and the data is available. One example from Enin is that we know a company has to have more than a certain number of employees to become a large customer of ours.
For you it might be that the customer has to be in a certain location, have a high revenue, show a particular financial development over time or belong to a specific industry. For most, it is a combination of these criteria. The essential thing is that the data is available and can be added from external sources.
If the customers can be identified, this data is easy to add and we can run a twin analysis. From that we can create the basis for a prospect list.
Analyze and assess risk
Level 3
You can work out which companies you ought to be approaching that are not in your customer base today.
This is where the time you spent on the two previous points really pays off. And strictly speaking, you do not get here without having done levels 1 and 2.
This is where the fun part starts. Perhaps you have already had a few eye-opening moments. The foundation is in place and you can start thinking about all the opportunities ahead.
The first thing you do is use your drivers to find out how big your market actually is. The more specific the criteria, the better the analysis. Once you have found your opportunity space, make sure you remove existing customers from the data set. Then you know what you are left with and can consider how your plan fits with it. You are now getting close to a basis for deciding a sales strategy, but we recommend that you stay with us for a few more levels...
In this case the number of employees is the single most important growth driver, and below you can see the number of companies we found in each segment after existing customers were removed from the data set. Groups A, B and C are suggestions for how to divide up customer groups. These should probably be approached differently. We will come back to that in the next blog post.
Level 4
You have the right internal data on what your customers buy, how often and when. Historical data/behavior is available for your customers, and you can put a figure on the value of the opportunity space.
This is called transaction data, and a so-called RFC analysis is often used here. It stands for Recency, Frequency, Monetary.
Recency: When your customer last made a purchase can say something about the value they have for you. If the customer last bought five years ago, in some cases they may no longer be an active customer. In other cases, for example if the customer has bought a car, it may be exactly now that the customer is in the mood to replace it.
Frequency: How often your customer buys can indicate whether this is a customer that generates recurring revenue or whether the purchase was a one-off.
Monetary: How much the customer spends with you over a year or across the whole customer relationship gives you the customer's total value. Perhaps the customer generates revenue across departments and product types?
At this level you may need to go back to level 2, that is, run an iteration and adjust your target groups.
Once you know what a customer is worth to you, you can also calculate what your opportunity space is worth.
A data-driven approach to prospecting can help you with every element in the model above, but it also requires people and systems to work together, for lasting change and a result that creates growth.
Level 5
You can give customers and prospects a score for how mutually attractive you are to each other . That reveals what level of service/priority the customers should have.
Using selected criteria (the ones that matter for your business model), you can give the customer an overall value score. You might score the potential for total revenue, the strategic value of having the customer as a reference, the customer's expected growth over the next 12 months, or how much value you can actually give the customer or prospect through your products and services.
You should then have what you need to divide your customers into different groups according to how they should be served or handled. Illustrated here with "Stars", "Shooting stars", "Friends" and "Randoms" .
This type of model is familiar to many. There are many versions of the BCG matrix. Here we have made our own version. An alternative way of reading the axis showing potential is as the customer's assessment of the supplier's strategic importance.
"Stars" are customers or prospects with high profitability and great potential. This is often where you find a handful of customers who need tailored solutions.
"Shooting stars" are customers with low profitability and great potential. They have the prospect of becoming "Stars" and should be served accordingly.
"Friends" are customers (or prospects) with little potential and high profitability. Most of your customers should sit here and give you continuous, recurring revenue.
"Randoms" are customers who may not fit into your defined customer segments, but who still need your services. You have not targeted them specifically. Typical customers in this category are the ones who buy a single tailored project and never come back to you.
Very many people get no further than this. In some cases that is absolutely enough, but we would like to show you the next 4 levels in the next blog post:
Data for action: Prospecting - Part 2/2
As we now move towards being able to alert and monitor, modern technology and data are our best friends. Plenty of tools have come along that we can build on, now that we have defined who we are going to approach and why.
If you would like to read more about data-driven sales strategy, take a look at this post.
Contact us if you would like to talk about how to prospect more intelligently!
