As a martech enthusiast, I can vouch that there are hardly any marketers or sales professionals today, who are not incorporating artificial intelligence in some way. 91% of companies with world-leading brand recognition and high levels of customer satisfaction use AI solutions to increase customer satisfaction, compared to 42% of companies in their fields overall. -MIT Technology Review and Genesys, 2017.
We all use Alexa, Google Assistant and more. But the question to ask is – Is AI enabling us? Is the impact measurable?
While some continue to doubt the outcome, AI has helped us get closer to the customer by making us data-driven. For example, machine learning has been long applied in search engines by industry leaders such as Google and Microsoft, thereby continuously improving the relevance of search results for the end users.
So, if you look closely, what this means to us as marketers is – the impact of AI will be directly proportional to the quality of data that goes in. In other words, the better you know your customers and prospects, the more relevant you are to them. It also means that the customer data needs to be enriched to prevent decay (industry average for data decay is 30% YoY) and thereby ensure it is useful to derive predictive analytics, customer segmentation, sales intelligence, insights and more.
Assuming, the data hygiene is taken care of, let us look at the 3P’s where marketers can benefit the most from AI:
One of the key metrics that a marketing team is measured by, is the prospect pipeline it creates. Prospecting is not about reaching out to your list by cold calling or emailing – it is about having real-time information on who is interested in your solutions and why. More importantly, do they have a budget for it? In a typical B2B scenario, where this information is even more difficult to get, an AI platform such as Fiind Smart Signals helps marketers and sales professional with signals on customer intent and product fit.
Now, let’s say you are running an ABM campaign – intent and fit signals are gold. You exactly need to know whom to target, why they would be interested, their stage in the buying cycle, etc. Since we touched upon ABM – here’s an ABM checklist that you can use as a blueprint.
Once you have adequate information on your prospects and existing customers, it is all about prioritizing and segmenting them. This is where machine learning algorithms come into play with predictive lead scoring and hyper-segmentation. This gives a very scientific approach to segmenting your leads based on their sales propensity compared to speculations whose results vary with the experience of the marketing or sales professionals. AI is not just useful in the case of prospects but also for your existing customers where you can identify upsell and cross-sell opportunities based on the signals they exhibit across several sources internal and external to your organizational martech stack.
Now that the “why” and “who” part is taken care of, let’s look at the most critical part – “what”. Why should a prospect or a customer respond to your campaign? Is it relevant to them? We’re in an era of hyper-personalization. Marketers need to move away from the market mindset and be focused on giving the individuals that comprise the market – a great experience. No one wants to be sold to, they want to be engaged.
AI can help you with at the right pitch for the right customer at the right time. At Fiind, we like to call this “pitch points” which typically is the bedrock of all inbound/outbound marketing campaigns and also the intelligence that helps salespeople in ensuring meaningful conversations.
To sum up, there is no question of whether AI will enable marketers. It is all about how we integrate AI into our daily marketing and sales operations. AI is not here to replace human beings, and the effectiveness of AI in enabling relies on how well we augment it.
Let me know what you think?