Analytics is far from straightforward.
Despite being such a growing service in today’s tech-driven world, analytics still tends to be a widely misunderstood industry. We recently sat down with Datamine Partner Mike Parsons to chat about some common industry misconceptions he's encountered throughout his years at Datamine.
1. “This one person knows about analytics – he or she can sort it all out.”
Strangely enough, many businesses tend to assume that one or two people with analytics capabilities will be able to single-handedly figure out the challenges faced by the organisation. Mike says he sees this quite often:
“There isn’t a lot of domain expertise in analytics just hanging around, so there’s an assumption that if you ask somebody who knows about analytics to help you, they’ll magically be able to ‘fix’ the problem – however, there are actually a lot of components to making it work right.”
In the situations Mike has seen work well, there has been a multi-functional team running the project. Even if the heavy analytics lifting is done by only one or two people, this sharing of responsibility allows for varying viewpoints and a much broader spectrum of expertise.
“If you were starting a new business line, you wouldn’t just say to one person, ‘okay go do this’ – it requires more than that, but for some reason in analytics people often assume that one person can handle the entire process.”
2. “To get our analysts to produce good work, we need to specify what they do.”
Another common misconception Mike sometimes encounters is that analysts need a lot of hand-holding throughout the process. There are a couple of reasons people assume this:
“When a business has a limited amount of analytics resource and there’s only a short amount of time that a project can be worked on, people feel like they need to be very prescriptive about what they want in order to get something achieved,” Mike explains. “A better approach, I’ve found, is to be thorough when describing the problem itself and the outcome you are looking for, not the imagined solution. If you give the analyst your challenge, they will figure out how to solve it.”
Analytics is a very iterative and nuanced service – the reason a business has hired or contracted an analyst is because he or she has the skills that other employees don’t. To get the best results, you need to give them all the background information they require, then collaborate with them as they use their analytics knowledge to find a solution (even if it’s a different approach than you would take).
“It’s interesting how often we see this in analytics, especially compared to other similar services. When you go to a lawyer, or accountant, or architect, you explain your problem to them and ask for their advice on how to fix it. You wouldn’t try to tell them how you would go about solving it – if you knew how to figure it out, you probably wouldn’t hire them in the first place! The same approach needs to be taken with analytics.”
3. “To do analytics projects in marketing, we need to start from scratch every month.”
As a marketer, one of your jobs is to make an impact in the market with your target audience, whether it’s below or above the line – traditionally, you have to think up a thing to sell, figure out the target audience, craft a campaign, send it live and watch the results. This cycle repeats itself month after month, yet many businesses don’t realise that they can save time and effort by creating reusable steps throughout their marketing campaign. Mike explains:
“Businesses will launch a new product (design the process, build the creative, figure out the deployment and send it out) again and again, but every time they launch something new they start over fresh from the beginning. What they need to start doing is say, ‘this thing that I’m doing – am I ever going to do it again?’ If not, recognise that and treat it as a one-off. If so, can I design a repeatable process using this as an example in order to streamline the process moving forward?”
In the moment it might be more difficult to create a reusable process, but you will get better at thinking this way. The framework of steps that marketing teams go through every month can be turned into a reusable set of tools, most of which should (hopefully) be applicable to the next product launch or campaign.
“This approach is especially important for analytics-heavy marketing campaigns, because having to do the exact same manual data work each time just to get to ground zero is really hard work,” Mike says. “I always encourage marketers to focus the most energy on anything they can use again, whether it’s reusable content, a reusable process or a reusable dataset – what it boils down to is the complexity of personalisation and the depth you need to go to with analytics in order to get real insight.”