Some companies are searching, grasping, hungry for just a few more leads. 

Other companies are generating an avalanche of leads. 

Neither scenario is ideal, and in both cases organizations will face the same challenge. 

No matter how many leads you’re generating, the trick is determining which leads will most likely lead to a sale so that you can inform your reps and get them to work on closing. 

The arrival of artificial intelligence (AI) may be the only thing that helps them achieve that goal, while also helping shorten cycle times and improving the overall marketing process. 

AI is often poorly understood — not because it’s inherently complex, but because it is perceived as complex. Particularly for those in sales and marketing, who are always under pressure to get more done and drive more revenue, the perceived time to learn what AI can do and how it relates to their jobs might be off-putting. 

Companies that succeed with AI not only recognize this but begin to help show where AI fits into their existing processes, including those that span sales and marketing. This could be things like the way AI is used to connect with a CRM like Sales Cloud and the various tasks that were once completely manual and often extremely time-consuming. 

If you picture the traditional org chart in many companies, for example, think of AI as sitting just below the rep, almost like a direct report. They might not have been “hired” by the sales team, and they shouldn’t require a manager as such, but the technology will provide value on an order of magnitude greater than even the best sales assistant. 

Of course, the end goal is all about helping achieve or exceed quota, but before we even get there, it might make things clearer to look at AI and lead generation from the very start of the marketing process and working our way forward:


A different way to think about demand gen

No one likes uncertainty, but too many marketing programs operate under a principle that could be summed up as, “Let’s try it and hope for the best.”

A campaign could include digital ads, for example, along with an email blast, social media posts and an event. If things go well, customers and prospects will respond by generating activities such as visits, shares and clicks. They might also wind up filling out a form or doing something else that effectively turns them into a lead. 

Before AI, marketing departments traditionally looked at all this retroactively, once they’d already passed along what were essentially their best guesses on qualified leads. 

This overlooks the fact that customers and prospects aren’t limiting the time they engage with a brand to the period when a marketing campaign begins and ends. They might be visiting your website every day, liking a post in your social feed several times a week or downloading an older asset from your online resource centre. 

AI provides a way to not only monitor that kind of engagement, but to use the data to adjust campaigns even once they’re already under way. This could mean tweaking the copy in an email to appeal more to a particular segment, or boosting the reach of a digital ad because one is performing better than the others. 

Using AI in this way helps improve the overall results of a lead generation campaign, while doing it in a way that comes across as relevant and responsive to your potential new customers. 


A different way to think about scoring

They opened an email. They clicked on a link. They spent two minutes looking at a landing page. 

Sounds like a super-hot lead, doesn’t it? 

Depending on how you develop your scoring, this might actually reflect what’s considered a “warm” lead from one that shouldn’t be passed on to sales. In some cases it might work, but it’s a limited way of looking at the behaviour of prospects. 

AI can spend the time on this that a human being simply can’t, treating every move a prospect makes online as one step in a nurture campaign. That doesn’t mean every move they make is successfully nurturing them into a lead, but AI lets you see what’s happening and take the steps that encourage the most desired behaviours. 

This also simplifies the scoring process and helps to make scores more accurate, which in turn allows marketing teams to pass on leads with greater confidence to the right rep.


A different way to think about routing

The importance of collaboration in almost all successful businesses today means marketers can’t just pass on leads and wash their hands of them. 

By helping pinpoint the leads with the highest propensity to buy, AI should create more effective handoffs between marketing and sales. In other words, AI will help ensure leads go to the rep that most recently engaged with a prospect, or a prospect with similar needs and characteristics. It will also help surface data about the time between a rep reaching out to a lead and actually converting them into a customer. 

Routing and matching leads though AI not only makes reps more productive. It makes them happier because they’re going to be focusing on the leads that lead to robust deals, along with relationships that could lead to cross-selling, up-selling and repeat business. 

As more organizations become comfortable with AI, they’ll also get better at fine tuning the top-of-funnel marketing phase so that reps can give this last crucial stage of closing all the attention it might need. 

The potential of this technology is something organizations of any size cannot afford to waste. It’s time to put AI to work on lead generation — not just to boost your business growth, but to make the work everyone in sales and marketing does more efficient, effective and enjoyable.