Yes, you read it right. Is customer coincidence possible? To answer that question – let’s understand what coincidence is. At the surface level, let’s say coincidence refers to a remarkable concurrence of favorable events or circumstances without an apparent causal connection.
The key word to take notice of is “apparent”. In other words, it is just that we have not noticed the possible connecting factors that lead to the concurrence of events. Thus, it is a coincidence only until the cause is unknown.
Now, put into a customer scenario. Given that customer experience is expected to be the biggest differentiator, and with GDPR expected to bring in a lot of changes in 2018 – can we depend on coincidences? The wiser choice would be to create favorable experiences, based on the understanding of the factors driving it.
Create coincidence by finding the connecting factor
Sounds oxymoronic, right? Once you know it, it is no more coincidental. The key ingredient of a successful product selling experience is to know whom to sell it to and if the targeted recipient has a need for it. Yet, at times the prospect doesn’t realize the need for it. For instance, let’s assume they are selling B2B software solutions. They might be looking for a way to sell more, optimize the spend to ROI ratio, increase revenue for a specific product line or more.
The simple connecting factor could be – picking up those signals that indicate they might need help and helping them in solving their problem.
Let’s broadly categorize the signal identification into four segments:
- Known-Knowns – When you have complete intelligence about their customer and also clear about how to help them.
- Known-Unknowns – You know that what is the missing link, but are unaware of the means to overcome it.
- Unknown-Knowns – You are aware of the opportunities but unaware of its potential, thereby under-estimating or over-estimating it.
- Unknown-Unknowns – There is lack of awareness of both the opportunities and the means.
How does Artificial Intelligence help?
AI platforms such as Fiind can help classify prospects into buckets/segments based on awareness and sales maturity. In other words, the classification is based on the prospect’s fit with your product.
This is where data science comes into play. Data, in broad terms, can be viewed into 2 categories – direct and observed.
Direct data is generally voluntarily shared information such as – a company’s business, social media handles, SEC Filings, event announcements, press releases, etc.
Observed data is something that is involuntary, but well within legal boundaries, that can be used in measuring the orientation of a company towards certain key business areas or scopes. These are observations/hints that can come from news, hiring patterns (for example – unfilled job positions over a time period), social listening (forum conversations, sentiment analysis, etc.), and more.
Converting knowledge into intelligence
Unless the “known” is put to use or applied appropriately, it can never become intelligence but stay put as knowledge or accumulated information.
With the power of direct data combined with highly insightful observed data, you can establish relevant conversations with your prospect. In this era of hyper-personalization – who wants to hear a broad generic sales pitch?
Never under-estimate the power of serendipity. The hook on the fishing line is the element of surprise that is created by the customized content, which most of the time the customers don’t see coming.
To catch them by a pleasant surprise not only impresses them, but also reflects the dedicated effort that goes into the data collection and enrichment. (Check out the whitepaper on Data Stewardship to know more)
To sum up, there is no coincidence, but collective engineering of incidents!