B2B buying has changed drastically in recent years. Buyers today prefer to remain anonymous until deep into their buying journey; they make purchase decisions in teams; and they're resistant to traditional marketing and sales tactics, such as email and cold calls.
All those changes mean that our old ways of finding and winning customers just don't work anymore.
Reaching modern buyers requires modern solutions, including massive amounts of high-quality data and the artificial intelligence (AI) needed to turn that data into usable insights.
For many marketers and sellers, Big Data and AI feel totally out of reach. But the truth is that they're not only more accessible than ever but also a necessary part of your toolkit for finding, understanding, and engaging with buyers today.
Here are four ways AI applied to Big Data in the revenue process can help businesses win more customers—no advanced technology degree required.
1. Surface new prospects to reinvigorate pipeline
Most buying behavior happens anonymously, in what's been coined the Dark Funnel—a digital realm filled with rich data about prospects and customers that we can't access without today's technology.
As buyers conduct their research on various devices, through different channels, and in disparate locations, they leave behind a digital trail of crumbs. If we don't have a way of picking up those crumbs, we're missing out on tons of prospects who are interested in exactly what we are offering.
Big Data solutions driven by AI make it possible for marketers to gather those heaps of breadcrumbs and match them to the accounts they're coming from. Then AI sorts through them, compares them with your historical win data, and tells you who in the universe of possible buyers is a good fit for what you offer. In that way, AI helps you uncover potential customers who otherwise would have gone unnoticed.
Being able to stay on top of difficult-to-track signals takes what was previously in the dark and turns it into a revenue moment.
2. Break into new markets and verticals
One way to get new customers is to expand into new markets. But figuring out which geo or vertical to expand into can be a daunting task.
In the past, without modern tech to support expansions, we'd end up in one of two scenarios:
- The first was analysis paralysis, leading to decisions made with the proverbial dart thrown at the wall.
- In the second scenario, teams would pour hundreds of thousands of dollars, and many months, into a consulting firm to help them plan an expansion.
But now, AI applied to Big Data can take the guesswork out of those types of expansions by showing you which companies are in the market for your solution in different industries, locations, etc., so you can determine precisely how much potential opportunity exists. And it can all happen in minutes instead of the months it used to take with manual methods.
That allows marketers to be much more agile—giving us the ability to keep our finger on the pulse of all potential opportunities so we can choose the best ones to pursue.
3. Improve efficiency and effectiveness of marketing spend
AI can accurately predict what stage of the buying journey prospects are in so that you meet them where they happen to be. That means you're not sending "Intro to Widgets" content to buyers who pretty much have a PhD in widgets, and you're not serving up "Buy Now!" ads to people who are just discovering that widgets are a thing.
So AI tells you what stage your potential buyers are in, then makes it possible to orchestrate highly personalized, multichannel experiences at scale. That means that you can serve the right message to the right people at the right time and across all the right channels (website, chatbot, display ads, email, etc.).
It also means you're not spending money delivering marketing campaigns or ads to people who are just going to scroll by. By listening to the AI instead of taking an old-school spray-and-pray approach, you can reduce your spend on ads and campaigns while also improving outcomes.
In short, AI makes marketing campaigns easier to execute and ensures they land in front of the right people (and only the right people) at the right time and in all the right places. The result is dramatic improvements to marketing efficiency and effectiveness with less waste.
4. Help the prospecting team identify and prioritize high-intent accounts
Time is a prospecting team's most valuable resource, and reaching out to accounts that are either not the right fit or not ready to engage is a waste of that precious resource. AI can identify the best accounts to work at any particular moment, which means sales/business development reps can prioritize each day with a list of in-market accounts that are likely to be receptive today.
An analysis of teams taking such an approach found that within just two quarters, prioritizing in-market accounts was 1.4 times more efficient than working accounts AI had not identified as in-market.
In addition to helping with prioritization, AI also makes it easy for sales and biz dev reps to reach out to all the right personas on the buying team. We know that modern buying teams for big B2B purchases consist of 6- 10 people, and we also know that the more personas we engage, the higher our chances of success.
AI, combined with Big Data, can provide reps with current contact data as well as rich insights about what these potential customers are researching right now. So reps are able to not only reach out easily to the right personas on those accounts but also deliver a message that is hyper-relevant and likely to resonate.
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AI and Big Data were once out of reach for all but the most technologically advanced marketing organizations. But as the technology becomes more ubiquitous, it's becoming an important and useful part of all of our daily lives.
For marketers, AI holds tremendous potential for helping us more effectively connect with more customers—with less cost and less effort.
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