The Cost, Return on Investment & Benefits of Marketing Analytics
By Kerry Guard on April 17, 2013
In our experience, many clients initially view analytics as ...
- A value add service, attached to additional lines of business
- Pre-packaged together with any kind of lead generation campaign
- A sinkhole of a line item in their budget sheets
Why is this? Again, in our experience ...
- Analytics have been presented poorly to the client in the past
- The client is presented with 30 slides worth of charts, graphs and numbers, but no real insights 'in between the lines'
- This leads analytics meetings to be ... *yawn* ... you get the point
What I've described above is more of a worst case scenario: the zombie apocolypse of an analytics meeting, so to speak.
In reality, properly structured marketing analytics plans can allow brands and agencies to break down the granular performance of their marketing efforts, pull out insights, and reposition their marketing funnel (so to speak) to incorporate those insights into their efforts moving forward.
We often break down the value of a strong analytics practice with the following sentence:
The price of light is less than the cost of darkness
Focus on data efficiency: Invest in actually knowing the solution instead of guessing a potential fix and throwing marketing dollars recklessly at it.
In this article, we will break down some key points to assess the efficiency of your marketing analytics practice. Specifically, we will focus on the costs and return on investment of your marketing analytics.
Identifying the Costs of Marketing Analytics
The first step in looking at the cost of your marketing analytics plan is to identify various expenditures of all the different systems your company employs.
This is achieved by identifying two cat of costs you should break down: one is what we call €œhumans€ and the second is €œtools€.
Human cost is the people-power behind your analytic systems: the consultants, full-time employees, or outside agency you hire to assist with the process.
In terms of costs, there are a couple of considerations. Look at specific projects and ask the following:
- €œDo I need to bring this in-house?€ If yes, you€™re going to be hiring full-time help. </span>
- €œIs the project one that can be outsourced?€ If so, there are two kinds of outsourcing€“€“single person projects (What is her/his cost?) or if it€™s a large amount of work that needs to be done, consider if a specialty agency is necessary.</span>
The other category of costs is tools (we call them robots here at MKG). These are the mechanical devices capturing and assembling your data.
Look across your organization and ask the following:
- What kind of tools do you need to measure your brand€™s analytics?
- What tools do you already have, how many people use them, and what tools do you still need?
Running a tool inventory across your entire company€™s analytics systems, detailing who is using which tool and for what purpose, is the most helpful approach to determining costs.
Additionally, analyzing your tool costs will help you spot duplications€“€“are multiple departments within your company using different tools for the same analysis€“€“and pinpoint paid tools versus free ones.
Evaluating the Return on Investment of Marketing Analytics
The hard part is out of the way; you've broken down your companies analytics budget and now know how much your tools & humans cost!
To tangibly evaluate the return on investment, we often calculate how much time our clients' €œhumans€ (employees, consultants, agencies, etc.) spend assembling data and pulling together spreadsheets.
How much time is spent assembling data every month?
For example, after running a similar inventory for one client, we discovered the following:
- Client spent approximately 50 hours per month assembling data (before any of it could even be analyzed!)</span>
- On average, client paid a blended rate (employees, contractors, agencies, etc) of $100 per hour
- 50 hours per month x $100/hour = $5,000
- It cost the client a total of $5,000 just to assemble their data every month. Not a single bit of analysis had been performed! We call this budget line item €œalmost opportunity costs€, as in we "almost had the chance to do something ..."
Beyond the money sunk into €œalmost opportunities€, consider if you had those 50 hours back for your employees, consultants and outsourced agencies? What could be achieved in terms of effective analysis; a step above that, those 50 hours could also be spent taking action, or making tweaks to improve performance, based on what the data is showing you.
Benefits of Marketing Analytics: A Real Example from Barack Obama 2008
A great study found that brands should spend approximately 20-percent of their yearly marketing budget on analytics. Most companies don€™t come close to that number.
A great example of a strong marketing analytics practice comes from the 2008 presidential election.
Barack Obama hired a campaign team chock full of data scientists to help execute A/B and multivariate landing page tests to boost online campaign contributions using one of our favorite tools, Optimizely. This team ran and measured a series of multivariate tests on President Obama's campaign contributions website and were able to collect the results and make optimizations almost instantaneously.
See a visual of this testing process below:
By making small changes to Obama's campaign contribution website, his team was able to see instantly what people responded to (or didn€™t) in real time.
So how did this perform? Having immediate access, being able to gauge what worked, and adjusting the website accordingly resulted in a seven-figure boost in campaign contributions for President Obama.