Friday, October 6, 2017

AI SPECIAL.... Improve your sales process with artificial intelligence and machine learning

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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