TL;DR
By adding additional insights and assumptions to a high-level goal we can create success criteria that give our digital strategy scope and buy in from the business. Success criteria also enable us to identify the initial research required based on our assumptions
Starting with goals
There would be no need for a digital strategy if we weren't trying to achieve some end. Often this end is stated as a high-level business goal such as 'reduce customer churn'.
A goal is a helpful baseline as it articulates why a business requires our digital strategy. When we formulate and present our digital strategy we do so in the context of helping achieve the high-level goal. For example, if our high-level goal is to 'reduce customer churn' then our strategy would likely focus on improving the experience of existing customers.
Our high-level goal also influences on the research we conduct prior to creating our digital strategy. In order to 'reduce customer churn' we would need to find out when and why customers are leaving our business. Our high-level goal is therefore a starting place, a solid baseline upon which to build our understanding of a businesses' context.
Why goals aren't enough
Although goals give us initial direction they are infinite. If our aim is infinite we can't know whether our strategy has succeeded or not. Perhaps by executing our digital strategy we 'reduce customer churn' by 20% over six months, is that a good thing? Should we stop and move focus on another goal? Has our strategy been a failure?
High-level goals also make it difficult to estimate the resources we need to deploy. By understanding the revenue gain by reducing customer churn we can justify resource allocation within our strategy.
The difference between success criteria and goals
Success criteria take a high-level goal one step further. They give a high-level goal specificity and context, allowing us to understand when we can move on or when we need to revise our strategy.
For instance, imagine we've been briefed by Vodafone, to 'reduce customer churn'. After investigating churn rates by customer cohorts we find that in our market, monthly customer churn is the poorest with customers on Vodofone's cheapest plan, $30 a month, by a large margin. We calculate that we can increase monthly revenue by $50,000 by decreasing customer churn in the $30 a month cohort by 7.5%.
We make an untested assumption that we can achieve the 7.5% reduction in $30 a month plan customers with a budget of $200K within 6 months, at which point we'll have an automated system in place to ensure the reduction stays in place. This means we are able to recoup our invested resources within 10 months of project commencement (6 months to reduce churn, 4 months to recoup the $200K at $50K per month). Based on our assumptions we also estimate the project will generate an additional $100K of revenue for the business within a year of commencement and $600K per annum subsequently.
Gaining stakeholder buy in
Armed with the insight of the company's highest churning customer cohort and some quick estimations and calculated assumptions we now have the beginnings of a business case to argue our case to senior stakeholders. Of course we still have many unknowns and assumptions, but we are in a far better position to understand the research we need to undertake in order to replace assumptions with insights.
The largest unknown is why are customers on the $30 plan moving on at such a rate? Our next step, prior to consulting someone in the executive function, is to create a plan to identify the best research method to uncover why this cohort of customers is leaving the company. We'll discuss how to structure such a research plan in a future article.
Armed with a research plan (methodology, expected outcome, budget, timings) we can now discuss our success criteria with a business stakeholder. We explain how we would first like to tackle the issue of customer churn, our assumptions around the initial project and what we need to begin with (the research). The stakeholder is now armed with all the information they need to either back the initial research or challenge our assumptions, which would be great as it leads to us being able to refine our assumptions based on the domain knowledge of the stakeholder.
Conclusion
Success metrics take high-level business goals and transform them into tangible frameworks upon which we can build our digital strategies. In order to develop success metrics we need to:
- Ensure you have a high-level goal from the business
- Develop insights around the high-level goals
- Create the success metrics by narrowing down the high-level goal with a set of assumptions
- Create the business case for a project to achieve the success metrics
- Identify the and design the research required to prove out your assumptions.