Is 2020 Crunch Time for AI and Automation?
November 11, 2019 • 7 min read
In the last few years, digital marketing has undergone a fascinating journey in financial services. As we have seen, digital marketing that puts the consumer front and centre has become a hugely important strategy for many firms.
For a long time financial services firms have suffered with a reputation problem, but the intuitive use of technology has allowed these brands to make valuable inroads into demographics they’d otherwise struggle to reach.
With 2020 around the corner, many marketing professionals are curious about what new trends and themes the next 12 months will hold. From our perceptive, the next biggest trend isn’t a new concept or the latest buzzword but instead a crunch point: that 2020 will be a critical year for how firms use AI and automation in their marketing.
A huge amount is written about AI but there remains a fundamental misunderstanding and what it can mean for a business (a recent survey of 400 marketers found 65% were confused over the definition of AI). Put simply, AI can be split into two broad categories; general and narrow.
General AI is what we usually think of with AI and is the stuff of science fiction films, with super computers outsmarting humans and eventually developing synthetic personalities. As exciting as the concept of general AI is, this is the part that people fear – will a new software program take my job? Would a self driving car crash? Can we trust computers that can think for themselves?
Narrow AI however, is the type of marketing software we use day-to-day. It's the system that identifies spam emails or enables automated conversations with website visitors, this is narrow AI. We've adopted many of these solutions including in our personal lives (through groundbreaking systems like Amazon’s Alexa) as well as in business. When we talk about 2020 being a critical year for AI in marketing, it’s important to stress we mean the latter category of AI not the former.
But, why 2020?
Next year is widely viewed as a crunch point for the use of tech in financial services, with PwC identifying tech and operating model upgrades as a priority for the sector. This is due to a number of trends, such as advances in tech and how its used, the demand for faster operating systems and the need for consistency across platforms.
For instance, there has been a wave of consolidation among the tech space that supports investment platforms (in July FNZ bought out GBST and in October Bravura acquired FinoComp). These kinds of deals mean organisations are having to mesh and merge different software models and in the long run complete overhauls may be required.
Increasingly, opportunities are being presented for AI integration in financial services. We could write entire blogs on how the combination of various narrow AI systems could increase efficiency in the back office sides of financial services firms. However, the most immediate and exciting place for AI is in marketing. And as it stands, usage of AI marketing has only scratched the surface.
We’ve already written about the importance of personalisation and how (narrow) AI systems are facilitating this, but more is required for AI to have a deeper impact. For AI to manage a full marketing campaign it would need access to immense amounts of data, a deep and holistic understanding of the products and services it was marketing and interface with many areas of the business.
Here we come back to the fear factor of AI. There is real concern here, we’ve already touched upon the challenges of meeting regulatory requirements in marketing, would allowing AI programs to access client data be a breach on GDPR for instance? When marketing products as regulated (and complex) as mortgages, investment funds and life insurance policies, marketing teams will of course be nervous about relinquishing control to AI programs.
There are also more real and immediate challenges. Finding people with the right skills and knowledge (specific to tech in financial services) to oversee such projects is a challenge. Once a team has the right skills on board, the process of combining a number of narrow AI programs into a holistic marketing campaign would be length and wrought with challenges.
However, if not 2020 when? In our last blog, we wrote about how the role of data centralisation and platform integration was driving customer expectation and the same drivers apply to AI and how it is used. Customer expectations are already being fundamentally altered and groundbreaking work from the likes of Amazon and Apple has already proven it has the potential to strengthen customer focus and improve retention. The financial services space, due to it's traditional and risk-averse nature, has already been reluctant to embrace some forms of technology in the past. The question is, if financial services continues to sit on the sidelines and not use AI, will there be missed opportunities and underserved experiences?
What can we do now?
Fortunately, there are things marketing teams can be doing now to begin to embrace AI and increase efficiency in their processes. First, review your current marketing practices and identify key problem areas along with some of the softer issues. Are any of these issues solvable through utilising AI and automation? Are there resource struggles or a series of repetitive tasks that could be automated with an intuitive AI system? For instance, is a certain newsletter you produce currently relying on manual data input? Could the mailing list for that newsletter be better personalised? This can not only drive efficiency but free up your team’s valuable time for the creative (and fun!) work.
The caveat here? Be careful not to deploy AI where this isn't a business goal or objective associated to it, this is will help firms ensure that they do not implement solutions for the sake of it.
Second, gain a thorough understanding of how AI could be applied to marketing in your specific sector. Whether its insurance, investment, mortgages or advice, a good place to start is to investigate what your competitors are doing in this area. For example, you can use tools such as Wappalyzer to identify the different technologies and automation tools being used on a website.
With customer experience becoming a huge focus, brands that can feed their experience-led data to AI will be able to explore new and exciting ways to better serve customers. There's an increasing number of AI systems and service providers available in the market today, so do your research and lean on them for knowledge. It may also be worth checking to see if your current CRM already has AI features baked into it you’re not using yet.
Finally, take some time and consider how AI could be embraced in your long-term marketing strategy. Take a step back and picture what marketing success looks like and then do some research to see how current AI provisions could help achieve this. For instance, ask yourself if media mixed modelling (MMM) analysis could be powered by AI in your business to deliver a crystallised view of what is and isn’t working? Where could AI complement your marketing implementation?
You should also identify what you want to keep AI-free, assigning everything to automation won't always be the right solution as there'll be times where focusing on traditional marketing practices will serve you best. AI will have different marketing applications for all businesses so there is an element of trial and error here in ascertaining what will work best for you.