If you’ve ever organized a conference, a tradeshow, or any B2B marketing event, you’ll know ensuring a good turnout is a lot like managing a sales funnel — only even more stressful. 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.
Then just pray everything goes to plan. (It won’t.)
One fundamental difference for B2B marketing events is that, unlike a sales funnel (or many B2C events), your event won’t 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 new 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. In fact, whether you’re launching a marketing campaign or planning an event, it all boils down to one crucial objective: identifying and engaging your target audience.
So when you’re planning for a major event, why not apply the same tools and approaches as you would to enhance any demand gen marketing campaign?
There are plenty of practical ways to do this, but one such tool in particular which we’ve seen work well in this application is Artificial Intelligence (AI).
Specifically, AI-powered Audience Modeling can help you identify your ideal customers, and then discover new, previously unknown audiences using an Ideal Customer Profile. That kind of methodology can also be applied to draw your ideal audience to any given event.
“Audience Modeling” traces patterns of previous behavior and characteristics from your existing leads and customers (or event attendees). Those common traits are then used to build a model of what your ideal customer (or attendee) looks like (Ideal Customer Profile) which enables you to prioritize your efforts by targeting only the most promising leads.
You can then score your leads by likelihood to convert, or any other number of criteria, 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 previous events will be good prospects, a significant proportion could be junior staff or interns, or other individuals (like journalists or bloggers) who may be interested in the topic of the event, but either possess no buying power or aren’t even affiliated with a relevant account. To avoid such data corrupting the predictive score, 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 their annual CX Summit by 95% using AI-powered Audience Modeling.
But utilizing AI didn’t merely increase their numbers — it also improved the quality of prospects they were drawing in.
In fact, such a large proportion of those new faces were well-qualified leads, that their 95% increase in overall attendance translated into more than triple the number of new client relationships established, compared to previous summits.
Learn how your company could attract more qualified prospects to your marketing events — download the free case study:
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