If you’ve ever organized a conference, or any B2B marketing event, you’ll know ensuring a good turnout is a lot like managing a sales funnel. You need to publicize and market the event, then convince people to buy tickets or, if it’s free, to simply get their butts on seats.
One fundamental difference for B2B marketing events is that, unlike a sales funnel, your event won’t typically end with attendees buying your product. Usually, getting people to attend is only the beginning of their customer journey.
Marketing events are there to generate interest, get people engaged with your company and/or product, and to network and build relationships. So whereas churning leads may be a concern at the sales end of the funnel, for your event you’ll want as many (relevant) new faces as possible.
Yes, having people come back again every year is very important too – particularly for building long-term professional relationships – but the dynamics and priorities are simply different. Reaching new audiences and generating more inbound leads is a key priority, even if only a fraction physically return to your event next time.
How artificial intelligence can help you draw new, qualified prospects to your marketing events
Still, the parallels are clear. So when you’re planning for a major event, why not apply the same tools and approaches as you would to enhance your marketing and sales prospecting more generally?
We’ve spoken before about how a predictive model can help you target ideal customers via an Ideal Customer Profile. Well, the same concepts can also be applied to draw your ideal audience to an event.
In a nutshell, predictive analytics harnasses the power of AI and machine-learning – ideally together with human input – to trace patterns of previous behavior from your existing leads and customers. Those behavioral patterns and common characteristics are then used to build an Ideal Customer Profile – i.e. a model of what your ideal customer looks like – which enables you to prioritize your efforts by targeting only the most promising leads.
Improve quality and quantity of leads
Predictive analytics also enables you to score your leads in order of how likely they are to convert, as well as intelligently segment leads for different campaigns.
It’s not hard to see how such a solution could be used to attract more of the right people to your company’s events. Incidentally, it’s equally clear – if not more so – why allowing for human input into a predictive model is so vital. While many people attending your events will be good prospects, a significant proportion could be junior staff or interns, or other individuals who may be interested in the topic of the event, but possess no buying power whatsoever. To avoid such data corrupting the predictive model, your marketing reps will need to weed out that misleading data.
Walker – a leading customer intelligence consulting firm – is a good example of a business which harnessed AI in this way. They increased non-client attendance at its annual CX Summit by 74% using AI-powered predictive analytics.
But utilizing predictive analytics didn’t merely increase their numbers – it also improved the quality of prospects they were drawing in, by applying an Ideal Customer Profile to this context.
In fact, such a large proportion of those new faces were well-qualified leads, that a 74% increase in overall attendance translated into triple the number of new client relationships established compared to previous summits.
By thinking outside the box, Walker used the same analytics tools other B2B businesses have utilized to generate net-new leads, in a slightly different context. And it worked.
Read more about Walker’s success with predictive analytics in our case study:
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