Being able to clearly articulate who your ideal target customer is can give you a significant market advantage, yet many businesses can’t easily explain who they derive the most value from and who they seek to serve.
Some businesses might be able to tell you they are a B2B (Business to Business) or B2C (Business to Consumer) company and that’s often as much as they can tell you without guessing if you push them for more detail.
If you don’t have a deep understanding of your customers and empathy for what they are trying to achieve, how do you know what to stand for in the markets you contest?
Knowing who your ideal target customers are means you know where and how to direct your resources (Time, money and effort) and help to give you focus for your business.
Advertising becomes easier when you know who you are talking with and your advertising dollar becomes much more efficient when your message is highly relevant to your audience. It’s a win/win!
Comparing sponsorship opportunities becomes so much easier when you know who matters to your business. Your staff will know exactly who to target and spend their time chasing and just as importantly who to walk away from.
The list keeps going….
So, how do you use a data-driven approach to determine and define your ideal customer?
It all starts with your data!
This guide assumes that you have a customer base with a little financial history to date, that financial history is where your data gold lies and there are several ways to extract that gold.
First off, we want to take a look at your revenue and analyse it, looking at the revenue by customer. Xero has some built-in reports that can help you to do this such as the income by contact report.
Generate a report comparing the last three months (Assuming no significant variances/seasonality) and export that reports to a CSV file to work further with.
Categorise your data
Now that we have a report showing your customers and how much revenue they earn you, we want to broadly categorise your customers (Segmentation) to begin building a profile of your best (and worst) customers.
Note, the approach is different if you are categorising a consumer or a business customer base.
For a business customer base, I use ANZIC code categories to help build a profile. You will either need to categorise every customer or randomly categorise a statistically significant representative sample population to get an accurate picture.
For a consumer customer base, you will need to use a segmentation model which slices the general population into different ages, stages and locations of interest, I’ve used the Genius model in the past via Reach Media, they no longer offer this service, but there are others available.
You should now have each customer (or a sample population) categorised in a standardised way by revenue over the last three months. Great!
Analyse your data
Now you can begin some analysis of your data to make sense of what your data is telling you.
First, we sort the data by total income or average income over the last three months from highest to lowest. Then we work out what is the high point, low point and median of the revenue and that determines who are our best vs worst customers.
Then we simply count each category representative in the best and in the worst band to determine the totals in each.
A tool I like to use, especially if you have many categories is the conditional formatting, colour scales function in Microsoft Excel.
Check the market size
Before you get carried away with what your analysis tells you, you need to also apply your categorisation to the total market.
This ensures that there are enough prospects in the market that you haven’t sold to yet that match the category or categories of customers that your data says are your best.
This data is usually easy enough to find on NZ Stats or ask for it from the segmentation model provider you used earlier.
What are the insights?
So now you have analysed your data, you should start looking for the insights as to who your best and worst customers are. Do you have any standouts in the best category?
I often use percentages to help explain and compare significance.
i.e. 25% of our best customers are in the professional services industry, and that sector represents 30% of the overall market in which our current market share is just 10%.
How about your worst customers?
Are there other sources of data we can connect to this data to enrichen it and provide more insights such as how much customer services time each segment uses?
How about applying the same approach to customers that have churned to gain some insights into loyalty?
Take your time and involve other people to help look for the patterns of significance and ask questions of the data to draw out other useful insights.
Tell their story
The final piece of the puzzle is putting your insights into action by creating a buyer profile and using this in your decision making going forward.
A buyer profile doesn’t just state which sector or segment your ideal target customer comes from but wraps a little bit of a story around your insights in a useful way.
This will help you and your team articulate who they are and what they look like, what they need, what they are trying to achieve and what they like about you.
A data-driven approach to determining your ideal target customer will give you extra confidence in your decision making and allow you to focus on the customers that matter to your business, can you really afford not to do this?
This guide assumes that all of your revenue is profitable. If you haven’t assessed your profitability you should totally do that, I’ll publish an article on that soon.