Improve your sales process with artificial intelligence and machine learning
Dr Anil Kaul, CEO and co-founder of
Absolutdata, explains how integration of artificial intelligence (AI) into a
chemical company’s selling process can uncover hidden opportunities and enable
them to more accurately identify prospects.
If a customer calls
and asks for chemical compound prices, that’s a clear buying signal. An email
inquiring about discounts on chemical products or a request to receive chemical
product specifications are unambiguous buying signals too. Chemical company
sales teams that receive such signals know how to respond.
But not all buying
signals are as clear cut. Signals can be too subtle for salespeople to notice,
or they can be hidden in large data caches, but failure to respond
appropriately can result in lost opportunities. This is where AI and machine
learning can help: AI can detect subtle buying signals and flag them for sales
team follow-up, and it can quickly analyse large datasets to identify
opportunities.
Generally, there are
two types of data in which subtle buying signals may be hidden. AI can help
detect signals in both types.
Finding Hidden
Signals in Internal Data
Chemical companies
typically have internal customer data like sales logs, website visitor
activities and purchase histories. They may also have data that yield patterns
that impact sales, such as seasonal buying and purchase sequence information.
AI and machine learning technologies can analyse internal customer data to gain
valuable insight in the following areas.
Sentiment: An analysis of sales
calls, emails, in-person meetings and other interactions can yield valuable
clues on what the customer thinks of the company and its products by detecting
signals in word choice, tone and sentences. Algorithms can provide summaries of
how buyers respond to offers, services, products and company information — data
that can be incredibly valuable to the sales team.
History, cycles and
sequences: Buying journey patterns frequently repeat, so an AI solution
that analyses the time of year and past purchase sequences can uncover hidden
opportunities. Sales teams can use this information to time their offers,
upsell or cross-sale activities.
Digital trail: Prospects who
download white papers, register for webinars and read a chemical company’s blog
are all signalling interest in making a purchase. Analysis of this digital trail
can let the sales team know the prospect is interested and give clues about
specific areas of interest.
Detecting Subtle
Signals in External Data
External data can
also yield valuable clues about buying intent with an AI and machine learning
approach. External data encompass everything from third-party sources,
including publicly available information about buyers’ companies, social media
activities and media content. AI analysis can shed light on previously hidden
signals in these areas:
Media analysis: Searching for
clues among press releases, stories about acquisitions, partnerships and client
wins can yield information that may indicate a buying opportunity. Media
content can also indicate when a client relationship is at risk, such as in a
merger situation where chemical company vendors might face consolidation,
tipping sales teams off so they can build a business case.
Social media
sentiment: An analysis of social media activities can reveal customer
attitudes on specific topics and provide clues that help the sales team present
the right solutions. If a chemical company detects that a prospect values
sustainability, for example, they can tailor a pitch effectively.
Adding Science to the
Art of Making a Sale
AI and machine
learning won’t replace sales teams, but they can help sales professionals do
their jobs more effectively. Humans can parse data to discover patterns too,
but AI can do it much more rapidly and effectively, freeing salespeople to use
their creativity and relationship-building skills to close deals.
When chemical
companies integrate AI into their selling process, they can uncover hidden
opportunities and more accurately target prospects. This creates a virtuous
circle, with customers receiving relevant offers and sales professionals meeting
or exceeding targets to accelerate company growth. By using AI and machine
learning tools, sales teams help customers, their companies and themselves.
Published: September 25, 2017
http://www.specchemonline.com/featuredarticles/improve-your-sales-process-with-artificial-intelligence-and-machine-learning
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