Space Aliens to Mobile Phones
Michael: “Did you explain school to him?”
Elliott: How do you explain school to higher intelligence?
Michael: Maybe he’s not that smart. Maybe he’s like a worker bee who only knows how to push buttons or something.
Elliott: [knowingly] He is too smart.
Michael: Okay, I just hope we don’t wake up on Mars or something surrounded by millions of little squashy guys
- E.T. the Extra-Terrestrial, 1982.
In the classic Spielberg movie, E.T. the Extra-Terrestrial, a young Elliott befriends a space alien and helps him escape the Earth and find his way back home. While movies have always pushed the envelope on what is possible in the future, technology hasn’t lagged too far behind. That dialogue between Elliott and his annoying older brother, Michael, evokes surreal imagery in the context of superior intelligence. Nearly all of that intelligence rests comfortably in our pockets, today.
Artificial intelligence (AI) is now, ubiquitous. From intelligent personal assistants to improved shopping suggestions, we experience the power of AI across mediums in various interactions. Enterprise, which had for long consigned such fantastical expectations of cutting-edge technology to consumer applications, has now begun to realise the potential of the little squashy guys.
Unraveling the little squashy guys
While Governments and policy-makers fear that AI and automation will replace jobs, algorithms continue to make work smarter and help corporations improve productivity to meet the rising demands and expectations of the market. A Terminator, doomsday scenario is what comes to mind as soon as AI discussions start.
Almost all rote, repetitive tasks can be coded away, or at the very least, made less rote and repetitive via automation – as has been the case for many decades now. With Machine Learning, it has now become possible to train computers. Trained with one or many data sets and, machine learning algorithms can reliably predict a desired outcome from a new, unknown set of data because of proper training. Much like how kids learn, computers are now beginning to learn and reason. This opens up immense new e possibilities for your business.
Much of this disruption has been enabled by data. Modern computing trends, such as Big Data and Analytics, are built to digest vast amounts of information about users, user behaviors & system behaviors to identify actionable insights that translate to improved quality of services by many orders of magnitude. From ordering food and booking cabs to payment transfers and smart wearables, our way of life has been completely revolutionised.
Data is the fuel that powers Machine Learning & Artificial Intelligence. It is oft quoted that data-rich companies will win while data-poor companies will struggle. So, look at your business and identify what data is generated but not captured? What if such data could be captured, fed to machines to identify patterns & reason?
While previously, all of this data would be in the heads of personnel engaged with the customer, much of it is in the cloud, today. As the cost of cloud computing reduces progressively, the feasibility of capturing, storing and processing this data increases disproportionately. Enterprises realise that this has immense application in the customer acquisition and management processes.
Transforming the Sales Cycle
From planning to closure, AI will transform sales. Whether it is intelligent scheduling, lead enrichment, smart notifications, productivity analysis or more accurate deal forecasting, AI will reshape every facet of the sales cycle.
AI will help sales teams gain a more holistic picture of their prospects and customers, as well as observe patterns in the sales process and enable personalized sales engagement at scale. Enabling sales teams, large or small, to deliver customer delight throughout the sales cycle.
AI will help Business Leaders make macro-level decisions with real-time insights from the field. Managers can proactively coach teams to achieve their quotas and executives can finally focus on core activities that move the needle. Let’s look at how AI will impact the typical Sales Cycle:
- Strategy & Planning
The difference between a top sales rep v/s bottom sales rep is, at a minimum, a trillion dollar question. And the answer lies, essentially, in what happens between calendar events. AI can help plan and optimise these activities for salespeople.
AI can compare salespeople’s typical days with those of top performing sales reps in the organisation and across the industry. The data can then be crunched to reveal intelligent insights about the schedule. Who should she meet? How should she prioritise prospects? Which one of her clients responds best on what days? What must she do today to improve their chances of meeting her quarter’s goals? What activities do Sales Managers & VPs think salespeople must prioritise?
- Knowledge & Research
AI can track all of the company’s accounts and contacts from various public feeds. So, for instance, a change in the professional profile page of a key contact can be flagged off to the respective sales rep as a potential action item.
The World is more intricately entwined now more than ever before and it is imperative for salespeople to be on top of metadata at the levels of the organisation and industry. With the continuing expansion of scope and depth of searchable content on public directories, all of this data is easily accessible. In fact, there are various services, today, that integrate data from multiple profiles and enrich account and contact data in sales systems to deliver Opportunity Enrichment inside your existing CRM systems. Simply knowing and acting on all of these data points could make the difference between mining an account further for increased revenues vs. a churned customer.
- Qualifying Leads & Opportunities
AI can compare leads generated by marketing with historical sales records and allocate the lead to the sales rep with best chances of closing that lead. Opportunity can be prioritised basis competitiveness, quality of engagement, responsiveness, affinity, and sales representative. This helps reduce sales effort on irrelevant leads while improving the probability of closure.
Over a period of time, intelligent allocation helps salespeople build expertise in products and sectors. AI can also benchmark sales rep performance with upper quartile reps so that they are coached to improve Sales productivity. Sales leaders can diversify their teams across products and services so that their efforts are optimized.
- Communication & Presentation
AI can record and analyse audio interaction in real-time; by using language processing and speech recognition algorithms, the call is parsed. Keywords that indicate positive or negative outcomes are tracked, and also the overall emotion of the conversation is measured. Based on this data, the call is scored and patterns are identified. The sales rep is offered coaching on the line of communication to use, keywords to avoid & keywords to watch out for.
Business leaders can avail micro level insights in everyday sales activities, understand skill gaps, correct them and help sales teams perform better. Leaders can also improve their deal forecasting and dynamically course correct basis real-time customer feedback.
- Quotation & Closure
AI can recommend a range of pricing basis buyer persona, account potential, organisation health, closure probability and historical sales data. AI can analyse customer response to the quotation and suggest appropriate follow up actions for salespeople. The system can intelligently recommend optimal products & services that have the highest probability of purchase and best possible gross margins.
AI can also simulate customer scenarios in real time in a demo environment. Salespeople will not have to depend on Delivery teams to customize products and services for prospective customers. Instead, they can provide contextual data and have smart applications realign metrics and dashboards to reflect a customer scenario. This will help collapse sales cycles, further, as prospects can understand the true value of products and services.
- Nurture & Engagement
AI can signal up / cross-sell opportunities based on usage data from existing products. Historical data indicates if a customer with an active usage of one or more existing products is likely to buy a related product in the suite. AI will auto-create new sales opportunities in the CRM and urge the salesperson to pitch to the customer. AI proactively seeks out sales trends that indicate how an account can be mined to deliver incremental revenues. And powered by the same data, AI maps out ideal customer persona, and identifies, prioritizes new opportunities within the CRM.
- Learning & Coaching
AI helps organisations move beyond implementations and focus on outcomes, instead. It analyses sales performance data to nudge her towards executing more high ROI activities, while also tracking calendar events, such as calls and meetings, to improve qualitative aspects of her approach.
AI benchmarks activities and approach of sales reps with top performing reps in their organisation and the industry. This helps sales reps realign their focus and also proactively upskill based on identified gaps, so she can become a better salesperson. AI, also, helps sales leaders focus on the correct metrics and make need-based interventions. Overall, AI enablement will drive meaningful use of sales and marketing applications.
An inevitable, welcome change
With all the brouhaha about AI replacing jobs, there has been much skepticism among Salespeople and the general public at large. But, as the many scenarios depicted prove, AI will empower and augment salespeople with additional intelligence, rather than make them redundant.
In fact, AI will let salespeople focus on more human attributes of their work, such as, empathy, higher order intelligence, and other aspects that may require an exclusively, human touch. If anything, AI will help salespeople be more human. Whatever be the case, AI is an eventuality and is here to stay.
Elliot: [solemnly] Stay…
E.T.: [puts his finger to his glowing heart] Ouch.
Elliot: [mimics the same action, tearfully] Ouch.
E.T.: [E.T. and Elliot embrace each other, then E.T. puts his glowing finger to Elliot’s forehead] I’ll… be… right… here.