How to create the perfect Ideal Customer Profile
13 April 2017
If you’ve been selling your product to a broad variety of industries and sizes of customer, it’s often hard to know where to focus your sales, marketing and product development efforts. Who should you listen to and who should you be chasing?
Within your customer and prospect base, there will be customers that just “get” you. They buy quickly, they renew and expand their contracts and they are willing to shout from the rooftops about your product. At the same time, your sales team needs to be comfortable selling to them and there should be enough of them to meet your goals.
What is an Ideal Customer Profile?
Ideal Customer Profile research helps you to work out what characteristics connect these businesses so that you can pay more attention to finding and nurturing the most profitable customers.
While an Ideal Customer Profile will always be unique to a given company and is dependent on a large number of variables, it can be defined as the target customer profile that sales, marketing and product development will be dedicated to over a certain timeframe.
How to create an Ideal Customer Profile
1. Gather all the data you can on your customers
At DueDil we gathered the following:
- Salesforce: contract values, expansion, time-to-close, win/loss ratios
- DueDil business data: sector, turnover, growth, employee count, region
- Product analytics: monthly usage, feature usage
- Third-party research: price sensitivity, buying behaviour
- Qualitative characteristics: business model, technology adoption
2. Decide which are your best (and worst) customers
This will be different for every business, but at DueDil we looked at characteristics like:
- Highest initial contract values
- Post purchase expansion
- Renewals and churn
- Integrating with our API or Salesforce connector in addition to our main enterprise tool
3. Look for correlations
Examine the data to see if certain factors are consistently present for your best and worst customers. Good starting points would be:
- Size (employees, turnover)
- Job title/team
- Sales cycle duration
- Win/loss for a specific segment
Tableau is great for iterating this quickly, otherwise Pivot tables will be helpful.
4. Create a shortlist of segments
If you are lucky, one segment will stand out clearly above all others, lit by a ray of light from the heavens. More likely there will be a number of clearly bad segments and then several equally promising ones. Define them as clearly as you can so that you can make objective comparisons between them. For example:
“Manufacturing companies with more than 1000 employees.”
5. Objectively compare each segment
Now you can score each segment based on the characteristics and questions below.
Your answers will probably be a blend of quantified data and qualitative feedback from your sales, support and research teams.
A. Product-market fit
- Which customers have the biggest problem that you can solve (in terms of time or money)?
- Was the customer aware that they had the problem and actively looking for solutions?
- How much did they save/make because of your product?
B. Sales efficiency
- How well do you understand the buying process of this customer type?
- How easy is it to get access to decision makers in these organisations?
- How long does it typically take to close a deal?
C. Addressable market
- How many prospects fit the above characteristics in your territories?
- What average deal size would you expect to achieve per customer?
6. Pursue the most promising segment(s)
This exercise will highlight which segment(s) you should be directing your sales and marketing resources towards. Inbound enquiries can be better prioritised, outbound campaigns can be more focused.
The scores will also identify segments that you should be going after in the future (“Future ICP”), when the product has evolved or when you’ve added new capabilities to your sales team. These are clearly defined levers that you can pull when you need to.
7. Create feedback loops and iterate
It’s not wise to go completely cold turkey from a very broad audience to one segment. We chose to go after a very clearly defined set of four segments. We then monitored them closely for signals (both qualitative feedback from the team and quantified measures from Salesforce) and made changes as required. This allowed us to de-prioritise one segment after less than a quarter had passed.
Whether you’re conducting your own ICP research or simply want to cleanse CRM data, DueDil’s industry-leading company data will help you better understand your customers and improve your internal processes.