53% of B2B organisations are using marketing automation technology right now, and another 37% say they are planning to implement it
Many brands are already deploying marketing automation. It’s not only popular for e-comm businesses, but also 53% of B2B organisations are using marketing automation technology right now, and another 37% say they are planning to implement it, according to an eConsultancy report.
But in the increasingly competitive battle to win the hearts and minds of customers – and to turn them into brand loyalists – automation can often be a blunt tool, delivering levels of personalisation which can be plain annoying. I’m personally fed up with ‘Hi Martin’ emails which are irrelevant, out of date or go beyond ‘nudge’ to jack hammer.
But AI can turn the jack hammer into a surgical instrument, enabling you to carefully create an empathy layer that connects you to your customers. So what’s it all about and how do you get on board the (fast moving) train?
Firstly, in the context of marketing, AI is a highly powerful personalisation tool which (especially given the demise of third-party data) helps you to maximise the value of your first-party data. Personalisation at scale is the new gold rush: real time, always on and of huge value. First party data is, as someone once said, “the new oil”.
AI or machine learning helps address one of the biggest problems for all modern businesses: you have huge pools of data (now becoming lakes), but you don't know how to get the most from that data, and you don’t have the predictive intelligence to mine it for the value that lies within.
Understanding its value and then making the right choice of DXP to realise that value will put you ahead of the game.
So here are three reasons why AI is so invaluable to marketers:
1. Personalisation at scale is impossible without AI
Rules-based personalisation is something we are all familiar with and is the basis for automation but can get hugely complex if our rules stack up. Humans aren’t great at working out intent and we are not great at maintaining rules.
When the rules get very complex, understanding which are of value is hard for humans to maintain and consider manually. The manual rules process is not great at scaling. The number of decisions required to stay relevant in one-to-one journeys becomes extremely complicated and manual rules won’t address the nuances of your customers’ intent.
2. AI helps you deliver relevance and loyalty
AI is particularly good at predicting a customer’s intent based on known behaviours and recommending what they should be doing next. With hundreds of thousands of customers and hundreds of thousands of messages – with content being constantly added and updated – success without AI is almost impossible. AI allows you to identify what your customers want and how and when to respond to that – in real time.
3. Get real-time value from your data
Swiftly and accurately turning your data into actionable insights is a challenge for all businesses. Adding AI to marketing automation can help you harness all your audience data to auto-optimise millions of experiences with precision. In short, you can turn all that data into strategic and tactical insights to drive more value in real time.
If you’d like to explore further examples of the uses of AI, Maria Yao writes knowledgeably in Forbes, adding dynamic pricing, testing and text generation among others to the long list of practical applications.
And here are three ways in which you can start to harness the benefits AI can bring to your marketing strategy:
1. Understand you will need to invest in smart people
While AI will take your automation to another level it won’t do it on its own. Machine learning tools need input. They reduce the time spent making manual rules-based decisions and they can start to predict intent in real time, but they need help getting there and for this you will need to dedicate some smart humans.
2. Start small, with focus
AI and customer journey optimisation work together to bring you real value, but you should allow your team to develop starting with small focused test areas to maximise your return. The marriage of content optimisation and NLP to understand where you might be over delivering can help to avoid all that manual tagging, creation of irrelevant content, and mitigate the concomitant potential for human error. Ensuring your machine is set up correctly on particular focussed tasks will help you learn together, avoiding pain and wastage.
3. Choose the right partners
Optimizely’s Intelligence Cloud, alongside their full stack DXP is a great place to start. Forrester reports that the Intelligence Cloud drives a significant reduction in the cost of unnecessary content creation with a 397% ROI and a break even on your initial investment in fewer than three months.
Ultimately you can understand your audience rather than simply logging page views – and with a better understanding of what’s working for your customers, you could see significant benefit to your bottom line.
Having experts to deploy Intelligence Cloud is no less important, and it's of course where Candyspace steps in.
It’s time to jump on board that fast moving train, then, but do make sure to travel with the right partner...
