It’s clear that data analytics and AI is changing people’s jobs. The role of the CMO as we know it won’t exist in five years. And there’s so much change still to come. We’re just at the tip of the iceberg.
Today, we obsess about measuring whatever we can to explain customer behaviour at each stage of the customer journey. For example, we measure open rates, cost per lead and the return on marketing investment for every activity undertaken. A lot of these tasks will be automated in the future. In fact, up to half of marketing jobs could be replaced by AI, machine learning and robotic process automation. These technologies can execute a lot of the activities currently handled by specialists such as lead nurturing, content aggregation, SEO, A/B testing, audience targeting, email campaigns, and programmatic ads.
Of course, all this activity will still need to be overseen by humans. And in some areas we’ll see growth. For example, with applying data science to marketing. All marketers need to become data obsessed by using AI to make smarter decisions. They also need to become more customer-centric.
Opportunities for B2B marketers
B2C is leading the way today with AI – and B2B has some way to go to catch up. But with e-commerce sales in B2B surpassing $1 trillion for the first time in 2018 and expected to rise to $1.2 trillion by 2020, who will be successful in creating a B2B Amazon-size business?
Marketers need to become tech savvy to remain competitive and must start this shift now.
In my view, the role of the CMO will be twofold going forward. Firstly, you need to be on top of your data. In effect to become a chief data officer, with a team of data scientists equipped to collect and analyse every piece of data.
Secondly, you need to obsess about the customer experience. Become a chief customer experience officer: one that really knows and understands the customer. Use all the data you have at hand to shape a better customer experience.
Creating the best customer experience relies on using the sum of the data that you have at hand, mixed with AI and human intelligence on top. If you do this right, you can create an ‘infinity loop’ of customer value. In essence it’s about: engaging with customers, collecting more and more data to feed the data analytics engine, using this data to create more insight and to deliver a better experience, and as a result, attracting new customers and making existing relationships stickier. This is a loop that can repeat over and over again.
Data is the basis for AI
AI is worth nothing if you don’t have the data. If your data sits in siloes across the business it’s not accessible. You need to build a common data lake where the data can reside and be put to use by AI. Next you need to augment the data with additional third-party data that adds further insight. This could include social data from LinkedIn and Facebook, and geo-location data, anything your customer gives you permission to access that helps you build a more complete customer profile. Once you know your customers better, you can start to provide personalised recommendations and insights and start to monetise the data.
If you think about the big tech companies like Google, Amazon, Facebook and Apple; they hold 1.2 million terrabytes (1,200 petabytes) of data. That’s a huge amount of data, and the value of their businesses rely on this data. Most B2C companies now have data science departments in place – in fact, according to top recruiting websites, the demand for data scientists has grown by 344% over the past five years. B2B needs to take action to catch up. If you don’t start the journey now you’ll be behind the competition.
So what can you do tomorrow?
I think the first thing is to be curious and play around. Build a small team of maybe five or six people, including data analysts, marketers and sales people. Define a business issue that you want to solve through AI and set the team a challenge to come back within two weeks with their proposed idea for AI. There are a huge number of AI tools in the market, covering areas such as automated content generation, customer persona profiling, chatbot technology, voice recognition, target audience profiling, personalised content creation, and insight trends. Go and test these tools. Be curious about how AI can better support marketing and deliver real benefit to your customers.
But also exercise caution along the way. Remember that AI is still evolving. Many algorithms incorporate bias because they are programmed by humans and learning from human interaction. If the testing ground is limited to one particular subset of a market, then caution must be exercised once it’s applied more widely.
AI is likely to be either the best or the worst thing ever to happen to humanity, so there’s a huge value in getting it right
Three tips for success
To start extracting value from AI, I’d recommend first:
- Getting your data right.
- Picking areas where AI, machine learning and robotic process automation will make a real impact for your business.
- Getting data scientists on board.
You need to hire talent, start to learn and experiment with AI. But never forget the end goal: use AI to support you in delivering a great customer experience: one that gives ‘unexpected delight’ to customers along the way. Happy customers will stay with you longer and buy more. AI will be crucial to achieving this success.
