The robots are coming! This is a recurring theme that has been permeating the cultural zeitgeist amongst professionals of all types, particularly marketers. Terms like ‘machine learning’, ‘blockchain’, ‘AI’, ‘chatbots’ and ‘virtual assistants’ can be found in most business or marketing publications but they often do little to help marketers understand in practical terms how to apply these technologies. The fear is that not only are the robots coming, but they are coming for my job. For many marketers who are not digitally savvy, the next wave of marketing digitisation is a frightening future to face.
Since the good old days of the Mad Men of the 1960s, marketing has always been about the acquisition of data to gain insights about consumers and customers, to influence new products and campaigns that drive business impact. The difference between those early days of Madison Avenue research and today is the scale and proliferation of data production and the number of measurement tools and pieces of martech to help interpret that data. We have moved from a time when it was extremely challenging to get any data on customers, when only a few elite brands and agencies had the ability to access that data, to having a tsunami of customer signals that most companies can now access, but which many marketers feel ill-equipped to capture and interpret into meaningful insights.
A question I often get asked at industry gatherings and marketing conferences is: “What are you doing in your marketing at Microsoft to leverage AI?” It’s a natural question, because as a company we are at the forefront of bringing artificial intelligence to the world. Our leaders have written books about the promise of AI (The Future Decoded) and the dangers (Tools and Weapons), and millions of web pages can be found with a simple search for “AI + Microsoft”. So, there is an expectation that our marketing teams are both on the cutting edge and experts on how to apply this in their work.
There is some truth, some aspiration, and some cold hard reality mixed up in that assumption. Some truth: on a global scale we are using dynamic lead scoring and machine learning to help us ensure that our sales teams are calling on the right customer at the right time with the right solution, based on algorithms and machine learning insights about whether our customers are in ‘buying mode’ and ready to talk to a sales rep. The reality: there are many people at Microsoft who can write that code and most of them are not marketers.
Where I ask our teams to bring value is not to write the code but to know how to articulate – to our teams who do – the killer insight they would like to generate. For example, the holy grail for a B2B marketer is to know the right tactic to deliver the right message to the right customer at the right time to move them along the purchase funnel. What our team is doing today is asking our developers: “Can you tell me which people in these sets of accounts are spending time learning about our cloud solutions? Are they in a position to make a decision about IT purchasing?” When they get that answer, at scale, they can then develop marketing campaigns and tactics to target those people with differentiated campaign messaging to influence their opinions about our solutions.
If you are a marketer and not working inside of one of today’s tech giants, what can you do? Two actions anyone can do: educate yourself and try things out. Chatbots can be deployed relatively easily in any company website – consider how they can be used at your company. Experiment with a small pilot, understand how your customers react to this experience, and build on that learning to create value for your company and your customers.
Are you using social listening and audience insights on your social media pages? Most social media outlets provide advertisers with a myriad of AI tools to interpret how users are reacting to your content. Spend time looking at the data, experiment with different tactics, and use the tools the outlets provide to gain insights. Marketers play a key role in evaluating insights around any data-driven business. They become an extension of the team to navigate immense amounts of data and pull out core insights suited for the target audience aligning to all marketing efforts. Therefore, data analytics, data collection and MarTech must work jointly to target the right audience for focused campaigns. This requires no purchase of MarTech, just some time and effort.
One thing that AI cannot do that marketers can is to take the initiative and try something new. Today. As the saying goes, you will fail 100 per cent of the time at the things you do not try, so marketers have nothing to lose by dipping their toes in the water and experimenting.