IBM Puts AI to Work for Partner Lead Sharing

(Pictured above: IBM’s European Digital Sales Center in Dublin.)

IBM continues to explore where to put cognitive to work for partners in order to create more targeted opportunities while improving outcomes for customers. The company’s latest efforts: using AI to speed partner lead sharing.

In late 2017, IBM started working with its chief analytics office — that’s where company data scientists know how to leverage cognitive and AI for business applications. These experts were tasked with mimicking the human lead-generation process. They built an engine called SCORE and paired it with human IBM lead passers to replicate the lead-passing process. SCORE went live last year.

Used to accelerate the lead-passing process with partners last year, IBM is taking the project a step further this year based on feedback from partners. The goal is to help partners improve their standing within the algorithm or get a better understanding of what they need to do to get better leads.

IBM’s Mike Fino

“This year, we’re beginning with the business partner score card; that will allow me as a partner to log in and see how I rank against my peer group,” Mike Fino, chief operating officer, IBM partner ecosystem, told Channel Futures. “Then there will be recommendations — either competencies I could take, or maybe, I wasn’t reacting to all of the opportunities that were passed to me fast enough. This is designed to help partners change their behavior and maximize their score within the SCORE engine.”

The beauty of this latest cognitive initiative is that it changes the partner’s behavior.

“To me, if it doesn’t change the partner’s behavior and get them excited about it, then it’s just another way to do what we’ve always done,” he said.

Getting partners to improve their position means better skilled partners with better quality leads getting passed to them more quickly.

“Everybody wins because partners are happier getting leads that are better suited to them versus getting more general leads. It also helps the partner be more productive because if they get leads that are more apt for their specialty, they’re not wasting time taking leads only to put them back into the system to IBM,” added Fino.

Earlier this year, at IBM Think, the company announced IBM Business Partner Connect, its first AI initiative to help the channel. IBM Business Partner Connect uses a Watson AI-powered engine to help partners tap into IBM’s global ecosystem to find partners with complementary capabilities.

This latest AI-powered effort targets demand generation and lead passing because quality and velocity are the No. 1 and 2 secret points to success — and AI tools promote quality and velocity.

Prior to this latest AI initiative for lead passing, IBM made several attempts to improve the human process with automation; however, they were system and program types of tools.

“Like anything else, if you don’t constantly change and update the tool, they can quickly fall out of currency,” said Fino.

The elegance of a cognitive tool is that …

… it continually learns. SCORE not only mimics the daily human lead-passing process and arms sellers with that info – picking the best partner for a specific opportunity – but factors in partners’ success or failure into the process.

In its first year of operation, SCORE contributed $100 million in additional revenue through the acceleration of IBM’s sales cycle, and increased lead passing by 50%, with a five-point improvement in the win rates on leads passed to business partners.

“Humans are still a part of the process. The tool makes the recommendation, and if within 72 hours our lead passing individual agrees with the recommendation, they can let it go and the tool passes it to the business partner,” explained Fino.

If the human lead passer doesn’t agree with the recommendation, they explain the reason so that the tool can learn, and the recommendation would be rerouted to the partner that the human lead passer thinks is better suited to the opportunity.

“So we achieve two things: We got the lead to where it belongs and we taught the tool that there was a different approach that could be taken so that the next recommendation would include that logic as part of the recommendation of the tool,” said Fino.

The AI tool also democratizes the lead-passing process to large and small partners, taking bias out of the process. So, for example, a small niche partner with the same capability as a bigger, more well-known partner business, has the same shot at getting a lead. That wasn’t always the case in the past.

SCORE looks more specifically at the opportunity level and pulls more partners into the equation. That also applies to adjacent opportunities.

“The old way was to give a lead in a different tech area – say the first lead pass was for security and the second was for storage – to the incumbent even if they don’t really have those skills. So, it may not be a fit. Today, this will allow another partner with a lot of storage expertise to come to the table, providing a better solution for the client,” said Fino.

SCORE targets all partners and opportunities across all IBM brands.

Partner-to-partner and the cognitive lead-passing initiatives work together, like pieces of a puzzle. But IBM isn’t stopping here.

The company has another cognitive application on its radar — adjacency selling. The idea is to help partners learn what has worked well for other partners in similar customer situations.

Here’s an example: “If a partner is buying product A, and product B and C [have] worked well for other partners in other ‘like’ clients – it helps partners make recommendations of adjacency offerings that have had success selling in other client engagements,” explained Fino.

Again, the beauty of cognitive is its ability to learn. Successful outcomes produce recommendations that are rolled out based on real-time information from the sales engine.