I run a MarTech company and everyone on our team clearly understands the importance and value of MarTech and yet, when I or someone else makes a pitch for a new addition to our stack, the first question my co-founder asks is “what’s the return on investment (ROI) if we buy that product?” It seems we’ve been discussing ROI a lot lately and because we’re a relatively small team a discussion usually suffices. A discussion won’t suffice as we scale, we need to bring more discipline and structure to the process so this week I’ve been researching (aka googling) how others approach this challenge. I didn’t find anything specifically related to MarTech but did find a number of articles1 related to calculating ROI for IT technology which were helpful.
For products where there is a tangible cost benefit in the form of new revenue, measurable productivity improvements, or cost savings, a straight-forward ROI calculation is workable.
The ROI formula
((Gain – Cost)/Cost) x 100 = ROI%
Some notes about leveraging this formula:
- Time period: Three years is the most common period for calculating gain.
- Costs: Costs should include all expenses to implement and manage the product for the three-year period not just the monthly or annual subscription costs. This includes training expenses.
- In calculating the gain and costs it’s important to consider the trajectory of both if you expect to add more product users over the three-year time period.
- An initial ROI calculation is a best estimate, the only way to validate the ROI is to implement the product and revisit your assumptions regularly over time. Measuring actual ROI will provide data that will be valuable in projecting ROI for new products that are similar in structure or value.
- Document your detailed assumptions, it’s the only way you’ll be able to revisit the calculation.
- Set standards where possible. For example: If you are calculating productivity savings you want to make sure that everyone in the organization is using the same hourly rate for each job function.
- If you are not sure how to approach this calculation, ask your vendor for help. They should understand the value they bring to your environment and anecdotal data from other customers.
- Some of these calculations will be complicated due to multiple quantifiable benefits. For example: When I look at my product, value can be quantified by reduced technology expenses, productivity gains, cost avoidance, and a host of additional minor elements. If you can get to a desired ROI without quantifying every single element then good enough. The more complicated and the more variables the harder to maintain. Focus on the elements with the biggest impact.
For some products it’s virtually impossible to quantify the ROI which has got me thinking about how to qualitatively assess the products in my stack and the overall stack itself.
In a previous life, I was involved in an angel investment group and one of the most difficult tasks in funding early-stage startups was to assign a value (valuation) to a company. There are at least eight different formulas (probably more) for calculating valuation but they all are calculated using company financials. In an early-stage venture, company financials are a best guess so any calculation done against those is going to be flawed. For that reason, most of the angel community relies on a combination of looking at valuations for similar companies and some form of qualitative assessment, the most common being The Berkus Method. The Berkus Method identifies five critical risk factors — idea, team, prototype, relationships/build-on-demand, and sales — and an investor assigns a dollar value to each based on the company’s progress in each area to reach a final valuation number.
A ‘Berkus Method’ for martech
We need a Berkus Method equivalent for marketing technology, a method that provides the ability to quickly assess the value of the products we use and the stack overall. Instead of assigning a cash value to each component, the idea would be to assign a rating. I’ve been thinking about the key components and have come up with the following as a first draft:
- Satisfies the use case for which it was acquired.
- Extensible to support additional use cases.
- Integrates with other products in the stack.
- Ease of deployment and use.
- Data contributor.
- Data source.
- Contributes to driving revenue and customer lifetime value.
- Contributes to lowering customer acquisition costs.
- Contributes to creating a positive customer experience.
- Contributes to customer engagement.
- Enables new marketing capabilities.
- Enables new marketing channels.
- Supports data compliance requirements.
- Enhances security.
- Critical to marketing.
For each component, the user would assess contribution on a scale (1 to 5 or 1 to 10) and then total the assessments and divide by the number of components rated. Not every component would be relevant to every product so the number of components rated would be variable product to product. Are these the right components? Should there be more or less?
I’d love some help from our MarTech community in refining this idea, finalizing the component list and thinking through how to extend this to create an overall stack value. Please reach out directly with your thoughts. Have any of you created something like this or an alternative within your organization that you would be willing to share? With more and more money being spent on marketing technology now is the time to jump on this before we are under or pressure to reduce technology costs.
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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.