In today's ever-evolving business landscape, having a data analytics function is a critical step for any organization looking to leverage data for strategic decision-making.
Successful marketing firms are fostering a data-driven culture in order to make educated decisions, personalize client experiences, and optimize marketing strategies.
But how do you start on this data analytics journey and build such a team within a business?
In this episode of The Undiscovered Metric, we speak to Tim Burr, founder and CEO of Scopic, a US software solutions firm that specializes in software development and marketing. With over 40 years of experience in the software industry, Tim is in a fantastic position to help answer this and many more questions.
Laying the foundation for a data-driven strategy
Building a data and analytics team within a business can be challenging for many reasons. It could be the lack of a data strategy, siloed data sources, outdated technology and tools. Perhaps it could even be a shortage of skilled personnel, or resistance to change from stakeholders, or what about the inherent complexity of integrating data across different parts of the business? Take your pick.
If you’re starting with a blank piece of paper, how do you start building a data and analytics function within a business?
Tim responds, “For us, I pushed it initially. I very much wanted to have a data-centric company, because I didn't feel that I knew everything, and I knew that there were secrets that needed to be uncovered. So we initially came up with a small set of metrics that were not so much on a per-department basis. I was in this for the long term, but our budget wasn't large, so we had to sort of scrape by and do what we could. We sort of refactored as we went along because we started on a shoestring budget and with a small set of KPIs.”
It’s clear that smaller firms may indeed face obstacles due to the high cost of analytics technology and software. But what if you're a bigger company and have more of a budget to play with? Tim continues, “Well, then you can take a step back, and you can say, ‘Okay, what do we want this to look like in a three to five-year time frame?’ Then what about a ten-year time frame?’ How many KPIs? What levels of dashboarding? Do we want to have departmental, all individual, corporate? You try to plan it out so that you're going to build something that's scalable and flexible and all that good stuff.”
To outsource or not to outsource
It is, of course, possible to hire data expertise to help build a strategy, but hiring analytics professionals can be expensive due to the high demand for their specialized skills and the need for ongoing training to keep up with rapidly developing technology. Reflecting on Scopic's early days, Tim shared their approach to this dilemma.
“Actually, we mostly figured it out in-house. Our team started out with a little more financial experience than analytics, but gradually they became a true hybrid finance analytics team. We didn't feel at that point we could bring in some expensive consultant to set us up here. So we did develop in-house, and we now have a team of about five analysts doing what's necessary to make sure we have data looking into all corners of the company.”
The importance of buy-in
Data-driven marketing has been proven to unlock value, with Deloitte suggesting businesses can, “increase sales from campaigns by 15% on average and double-down on their return on advertising spend (ROAS).” The rewards are clear, but the hurdles remain. We asked Tim about the biggest challenge he faced.
“That’s getting buy-in, especially getting department heads and maybe second-level leads and managers to really pay attention to the data. For a while, we had the data there for most departments, and it was like, if a tree falls in the forest and no one hears it, did the tree really fall? If the dashboard is there and no one is paying attention to it, is it really measuring anything being utilized? So it's taken time to reengage the department personnel to say, ‘Is this the data that you feel is capturing your story and measuring the most important things’?”
Marketers often face an uphill battle in getting buy-in from the C-suite and managers for data analytics. This can be due to concerns about the reliability and quality of data, existing biases or reliance on intuition over data-driven decision-making, and apprehensions about the potential disruptions to established processes and hierarchies.
So what’s the trick? “To really get buy-in, you need to start setting targets on a quarterly basis and having those actually in the visuals. We're now at the point where they're accountable for those targets, and that has gotten people's attention and accountability. There's alignment from top to bottom that these dashboards and these KPIs are important. They're going to be one aspect of how you're measured and it's important information to communicate all the way up the chain to our board of directors.”
Deciding the key metrics
For new analytics teams, establishing the right metrics from the get-go is essential for tracking KPIs like customer acquisition costs, ROI, website traffic, and lead conversion rates. This data informs strategic decisions, guides resource allocation, and helps in demonstrating the impact of marketing efforts to clients. But how do you decide on the KPI and then identify the key metrics that will determine the success of that KPI? For Tim, it wasn’t always an easy path.
“It was it was a lot of triaging between management, myself, sometimes the COO, the data analytics department, and the department we were developing the KPIs for.”
“We would brainstorm with marketing and say, ‘Okay, everyone come up with the KPIs in the three groups that you think are important,’ and then we’d put it all in one pot and gradually narrow them down. Sometimes, KPIs would be tossed or we would have phases of implementation indicating priority groups. Some would be merged, some would be changed. It was very collaborative and very iterative on a department-by-department basis.”
Marketing firms need to adapt and monitor their metrics continuously in a chameleonic way, modifying themselves and their data to changing environments and drivers. Iteration and learning from it can foster a culture of experimentation and innovation, meaning marketers can be confident in trying new ideas, learning from their failures and successes.
Using data to tell your story
With all of his experience and many successes, we had to ask Tim if he had any final tips for us.
“Don't fall in love with your metrics. You have to be prepared to say, ‘Okay, these things aren't working let's toss them out’. Having a big set of metrics can look impressive, but it takes time to maintain them. You can get a bit of metric bureaucracy, so you have to sort of guard against that and constantly pare it back to what's minimally sufficient. That's the core thing. It's a good exercise to get down to the minimal set of KPIs that are really telling the story that you need told.”
Whack-a-mole, herding cats, juggling eels. Getting your hands on the right data can certainly be all of the above. Yes, establishing a data analytics team in a marketing company can be demanding, but it can be highly rewarding. With a skilled team in place, companies can effectively optimize their user experience and sales funnel for increased conversions, leading to business growth and long-term success.
