Imagine you’ve bought an expensive new car. You’ve paid the tax, the insurance, services and MOTs, and you can’t wait to take it out onto the open road but yet third gear is the highest you’ve been able to get it into and that’s when it’s not just sitting on your drive. You know where the open roads are but somehow, you’ve just not quite made it out onto them. Not only have you not got anything out of the initial upfront investment, but all the ongoing running costs are going to waste too. Worst of all, you’re just not having any fun.
It’s madness. Yet time and time again, it’s exactly the sort of behaviour that’s happening in marketing teams across the world and while the business case stands up, the practice is completely unjustifiable.
Irrespective of sector, huge investments are being made in marketing technology. Up from 22 per cent of the budget in 2017, technology now accounts for a whopping 29 per cent of the total marketing expense budget, making martech the single largest area of investment when it comes to the department’s resources and programme, according to Gartner.
But that technology simply isn’t being used in the right way, or for what it was designed. Flash new cars are just sat on driveways the world over.
Off The Drive And Onto The Paddock
We’ve been promised that integrating technology into marketing activity will provide the scale to reach a broad audience in a cost-effective manner. So, we invest in new systems and services that promise to provide greater functionality, surgical precision and hyper personalisation. Yet how often are we able to access those game-changing benefits?
It’s a question that applies across all business operations. The average UK desktop holds £170 worth of unused software – these are applications that aren’t being used to their full potential, if at all.
What does that look like in marketing? A good example would be a country marketing team within a global company who use sprawling CRM and marketing automation systems to download CSV files only to send single emails. It might be a major retailer, with a significant multi-channel presence launching a marketing campaign, but only able to execute using one channel again and again, unable to crack the omnichannel code.
In each instance, marketers have deployed expensive software and haven’t been able to use it effectively. It might be because it is too complicated, or they don’t have the relevant skills resulting in grand plans coming apart at the seams with applications being deployed incorrectly.
Sometimes it’s as simple as not having the data required to use it properly. Whatever the reason, this inability to fully utilise martech is not only negatively impacting marketers’ effectiveness, but also hampering the ability to realise a return on investment.
To go back to the car analogy, it’s cool to own a race car, certainly; less so to never get it near a racetrack.
So, what’s the solution? Firstly, the reason why software isn’t being used to its full potential needs to be identified. Is it because it needs prepopulating, or that the data we have is incomplete, or are we lacking the right skills in the team?
In each of those instances, the real challenge is a lack of time. Loading the right data into a system, cleaning information so that it’s fit for purpose, or upskilling a team on technical details – all of it takes time – and time is money.
It’s also additional work, which in turn leads to a poorer user experience and decreased adoption rates, ultimately resulting in less of a return on the investment.
The solution, therefore, is to find a way that can speed things up. A way which could digest some basic information and then, using pre-established knowledge, populate the software so that end users are effectively coming in at a higher entry point. The teams actually using it could then spend less time on the set up and more time on actually using it, tweaking as they go.
The ability to do that sort of task is already in use in marketing. Artificial intelligence (AI) and machine learning are being deployed to make sense of the vast reams of data businesses capture and enable deeper levels of personalisation.
In this instance, however, it is less about engaging with the customer, and more about letting smart technologies find the data you don’t know you need, to prepopulate empty software with the right information, and to understand what’s required and what’s not, when information migrates from one system to another.
This isn’t a case for replacing marketers with AI – far from it. It’s about augmenting a human workforce’s natural creativity and empathy with technology. Lack the skills to use the software effectively?
Deploy machine learning to focus on the technical aspects, thereby freeing up those human soft skills to deliver what they do best – strategy, content and creativity – with industry best practice built in.
Eat My Dust
We’re only going to see more technology in marketing, not less. It’s therefore critical that we ensure that what we deploy is going to support teams to do their jobs at a level that delivers real return.
By harnessing AI to make onboarding and the user experience easier, marketers can overcome the complexities of new services to start using them quickly, upskill their teams in the process and in turn achieve true value much faster. In other words, not just getting the car off the drive but ‘dropping the hammer’ on the track.