NEW YORK: Cisco, the technology company, is using a "predictive intelligence" platform to gain deeper insights into prospective customers – and also into potentially effective marketing and sales tactics.

Sean Beierly, marketing manager at Cisco – a firm that makes products ranging from servers and routers to collaborative software – discussed this subject during a webinar held by 6Sense.

And he championed predictive intelligence, which crunches big data feeds like digital browsing behaviour, online searches and past acquisitions, to profile prospective customers in real time.

It can also establish precisely where these potential buyers sit in the purchase funnel, helping Cisco identify the types of communication that might best be employed to reach and engage them.

"We developed tiers – and the tiers are essentially maps to a destination based on the probability of those predictive leads to convert," Beierly said. (For more, including further insights, read Warc's exclusive report: Cisco peers into the marketing future with predictive intelligence.)

"The cream of the crop, top-percentage predictive leads could go direct to sales; the next tier of leads could go into a call blitz or marketing campaign where there's content or offers that can help to stimulate the purchase activity."

Each "tier" is placed into a wider context by mixing Cisco's first-party digital data with third-party statistics provided by 6Sense, which is a predictive-intelligence specialist.

"Our other scoring models had primarily been focused on activity inside of, and that's important. However, it's also important to have visibility beyond our own storefront," Beierly said.

"If you can understand insights about your customers' digital journey in that broader sense, it could really help you to uncover opportunities that you won't necessarily aware of."

And he suggested that the predictive platform – which automates a process previously relying on largely manual attempts at ranking leads – holds out significant possibilities as it develops further in the future.

"The models and the algorithms – they do that for you," Beierly said. "And they do it at a scale and a level of granularity that just can't be beat by a human."

Data sourced from Warc