Sales doesn't seem Mature for Automation, But it is
Mahesh Pardeshi
3 years ago
Table of Contents
Algorithms cannot sell like a human being, but they can teach us on sales fundamentals
AI CAN’T HOLD A CONVERSATION, BUT IT CAN ANALYZE ONE
MEET THE ALL-SEEING AI COACH
THE AI-ENABLED SALES SOFTWARE MARKET
1. DRIFT
2. INFER
3. GONG
WHAT’S NEXT FOR CONVERSATIONAL INTELLIGENCE?
Algorithms cannot sell like a human being, but they can teach us on sales fundamentals
Modern-day sales are
more about long-term customer interactions than big, one-and-done deals.
This has always been
true — smaller customer churn cuts promotion charges — but
it’s especially true today, as everything from designer
clothing to SaaS products moves toward a subscription model.
“The best way to be effective
in sales is to understand yourself, know your customer and know how you create
strong interactions with other people,” Samantha Harrington opined in Forbes.
“Once you’ve built that
relationship, shown you care and won their trust, you are on the road to
making a customer,” Lee Ann Obringe wrote in HowStuffWorks.
Building trusting,
enduring relationships does not sound like a process ripe for automation.
Machine-learning algorithms can master repetitive, predictable, and, in a word, mechanical tasks
— but despite the future foretold by Her, artificial intelligence has not yet understood
to empathize or make jokes.
Yet AI tools have taken
the sales world by storm. The key to their popularity? They automate almost
everything but actual
socializing.
“I want tech-enabled humans, not human-enabled tech.”
“I want tech-enabled
humans, not human-enabled tech,” Jim Benton, CEO of Chorus.ai,
told Built In. “I want the human at the front and center.”
Chorus.ai software
sticks to that vision, offering salespeople AI-based coaching and recapping of
their calls. It surfaces tactics that have worked with similar clients on past
calls — which could mean underlining a specific product feature or talking
less and listening more.
Benton calls this
“conversational intelligence.”
AI CAN’T HOLD A
CONVERSATION, BUT IT CAN ANALYZE ONE
Based
on the assessment of five million sales calls from more than 300 companies,
Chorus.ai recently circulated a round-up of macro trends in sales calls in the report called “The State of
Conversation Intelligence 2020.”
A smattering of findings: The average sales cycle takes 91 days, and it takes the
average sales development representative roughly 106 cold calls to schedule one
meeting. On successful calls, salespeople tend to speak for 40 to 60 percent of
the “talk time,” and always set next steps, which Benton calls “a critical
component.”
On successful
calls, salespeople tend to speak for 40 to 60 percent of the “talk time,” and
always set the next steps.
(If
Chorus.ai cannot see a rep planning next steps in a call, it flags that call in
red.)
Since
shelter-in-place orders rolled out across the country to combat the
coronavirus, the structure of sales calls has also shifted slightly, Benton
noted. For one, CFOs have been invited to 91 percent more sales calls. For
another reps have begun moving into their demos an average of two minutes
later than they used to — likely because salespeople are doing longer check-ins,
or “doing a little bit more empathy.”
These strong
trends aren’t the company’s bread and butter, though. In The Long Run, the
ideal sales plan differs depending on the product and the clientele. Chorus.ai facilitates
companies find their own, personalized best moves, offering salespeople
tips based on tactics that have correlated with success on their company’s
other sales calls.
The software calculates
success, or lack thereof, through an integration with the client’s CRM. There,
it tracks which calls move a deal through a sales channel or communicate with expansions
in a contract's price tag.
It drives
backward from there, checking successful video call footage, via Zoom
integration, for intelligence. It finds trends among the successful calls
— phrases and strategies that crop up again and again — and encourages
sales reps to try them out.
You could say it
is automating management, but let’s be honest: No manager has time to listen to
all their salespeople’s calls.
MEET THE ALL-SEEING AI COACH
In
the era before AI, coaching meant a manager sitting in on a few randomly
selected sales call, or overhearing snippets of dialogue from afar and
weighing in. Software like Chorus.ai opens up new possibilities — like
coaching on every call.
The software offers two types of AI-powered feedback: recommendations before a call
and recaps afterward.
It
surfaces recommendations by compiling playlists of calls that have worked
in similar situations in the past.
“We
could build a playlist of the deals we’ve won in the mid-market category [where
prospects] have had [certain] types of objections,” Belmont said. “We would
just build an auto-curated smart playlist.”
After a call,
the software can highlight key positive and negative signals from the prospect;
if they brought up your competitors an above-average number of times, for
instance, that’s not great. It can also highlight important metrics, like
the percentage of the call the salesperson spent speaking, the number of
questions they asked, and any traits that make the call quantifiably an
outlier.
Benton worries this could be “distracting,” and corrode “the human
connection” between reps and prospects.
Instead, it functions more like game tape for an athlete. It lets
salespeople review what worked and what didn’t on calls across their team and
send key excerpts of their conversations to other teams. If a prospect has
product feedback, a rep could forward that audio clip to the product and
engineering departments. If a section of the call went in an unexpected
direction, a rep could send that clip to their manager, who could then cite
specific, time-stamped moments in their feedback.
Essentially, Benton said, the software turns the sales call into “an
empowering event that helps mobilize product, marketing, support, engineering,
and leadership teams,” rather than what it once was: an “interaction that
disappears into thin air.”
THE AI-ENABLED SALES SOFTWARE MARKET
In 2018, McKinsey reported that AI could create more than $1.4
trillion of value for marketing and sales teams. That is thanks in part to
these companies, whose software applies AI to different facets of the sales
effort.
1. DRIFT
Lead
Qualification Chatbots
Drift’s
chatbots, Wall-E-esque cartoons that hover in the corners of companies’
websites, function like employees who never sleep. Around the clock, the bots
conduct preliminary conversations with prospective clients, pushing qualified
leads into the sales team’s pipeline. The company’s conversational AI is
powerful enough to recognize questions phrased as statements or execute account-based marketing tactics, like greeting top
prospects by name.
2. INFER
Lead Prioritization
Infer helps salespeople decide which lead to call next. It sounds like a simple proposition, but as Benton noted above, reps typically make more than
100 cold calls to set up one meeting — which means they still bark up a lot of wrong trees. This software sorts prospects into an intuitive matrix,
unleashing AI on client data enriched with in-house data from Infer, which
captures millions of different companies’ sizes, demographics, and tech stacks.
3. GONG
Revenue Intelligence
Gong’s revenue intelligence software offers salespeople real-time, AI-powered feedback on their calls, alerting
them to client traits like price-sensitivity. More broadly, it functions as a
user-friendly source of truth for sales teams, ingesting data automatically
through integrations with Salesforce, Microsoft Teams and more. On the platform,
users can easily scan all the sales in progress across their company, and
managers can browse benchmarked assessments of their reps’ calls.
WHAT’S NEXT FOR
CONVERSATIONAL INTELLIGENCE?
Conversational intelligence inherently improves over time. That’s just
the nature of machine-learning algorithms — the more a client relies on
them, the more deeply they understand “the voice of the customer,” as Benton
puts it.
However, Chorus.ai won’t just lean on its algorithms for product
refinement going forward. The company has two big plans in the works,
according to Benton. One involves exploiting the “video” aspect of video sales
calls. Though Chorus.ai can spot the difference between a talking head and a
slideshow, in the future, the product team hopes to improve its sentiment
analysis capabilities, so it can “see” laughter and non-verbal empathy cues.
“We want to help capture all the different interactions that sales teams
are having with their prospects,” Benton said. “I think the focus is just: How
do we make sure that you’re bringing the best of your company to every
interaction?”
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