How AI is Impacting Sales, Service, and Marketing

The core technologies of Artificial Intelligence (AI) have not changed drastically over the past 20 years. The techniques of the past fell short, not due to inadequate design, but because the necessary computational capacity, raw volumes of data, and processing speed just weren’t available or didn’t exist. The continued exponential increases in computer power and decrease in relative cost (Moore’s Law) coupled with vasts amounts of information collected from sensors and crawlers are catapulting AI to do extraordinary things.

“By mining the patterns that are happening in the marketplace, tying that back to relevant news, tying that back to tribal knowledge within the team—it gives you a competitive advantage.”
– Ray Wang (Principal Analyst, Founder, and Chairman of Constellation Research)

Customer acquisition, the customer experience, and customer retention are all make or break stakes for companies and Sales, Service and Marketing across all industries are looking to AI as the key to innovation, growth, and the discovery and creation of new business opportunities.

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The Impact of AI on Sales

The evolution of machine learning has allowed us to study patterns and see why certain salespeople, methodologies, actions, stories, and presentations are more effective. Whereas in the past a lot of selling was by gut, today we have empirical proof of what works and what doesn’t, and the most progressive companies are leveraging this to beat their competition.

With more sales data available than ever before, Chief Revenue Officers can learn more about a rep than previously possible. AI can analyze the data from rep interactions and use that information to better tailor training sessions so that onboarding time is reduced.

Machine learning will eventually be able to report on how well a rep responded to their training based on their performance and from there determine the most effective subject matter for future sessions.

By capturing all historic content and activity combinations across the enterprise and marrying it with CRM data AI solutions can show Sales Leaders the DNA of their top reps. For example, seeing what a top rep does and how they drive conversations with their prospects allows Sales leaders to pinpoint what the top 25% are doing that the bottom 25% are not.

What would a 25% improvement in sales productivity mean to most companies? It’s the difference between hitting and missing goals.

The Impact of AI on Marketing

AI is about to change the way we market. AI promises to shine a light on marketing and show if their strategic efforts are impacting the business and also to show if the products and services where marketing teams are spending their time are aligned with the priorities of the rest of the company.

With the rise of MarTech most companies have a heterogeneous marketing technology stack and have invested in everything from collaboration to automation to tracking.

However, many CMOs admit that their biggest problem is not the execution of campaigns or the development of content, it’s understanding the results; seeing the signal from the noise. Without understanding, just like salespeople, CMOs need to make a lot of decisions based on their gut. Without a signal they have no idea of reactions to products in the marketplace or what will lead to revenue and they are stuck living in a world of false-positives and false-negatives.

Marketers will be able to see holistic results in real-time. And this gives marketers the power to see the impact of context in a campaign and to deliver a more personalized service and experience.

The Impact of AI on Customer Service

It’s critical to deliver customer experiences that feel connected, memorable, and personal so at companies today service is really part marketing, part service, and part sales. It’s everything that happens after selling to the customer and customer success is really about all of those things that get a customer to come back and renew. This process requires a lot of care and AI will deliver new insights to make service more profitable.

A typical service representative produces hundreds of pieces of content (emails, spreadsheets, tickets, reports, presentations, notes) and consumes tens of thousands of pieces of content annually. However, service delivery is a fast moving function and products, workflows and information change all the time, which makes it impossible to keep up to date with all the latest rules and content.

The complexity in today’s service cycle is massive and to comprehend it you would need to absorb all the activities and permutations of an engagement. Most activity happens outside the service management software – no matter how well they are designed or maintained. Meetings, presentations, emails, attachments, phone calls, follow-ups, all this content and activity lives across email, laptops, drives, CRM, portals, learning systems, departments.

AI helps service teams develop loyalty and create relevant engagement points by interpreting a combination of natural language queries and user context to determine a user’s need. AI relevancy calculations sift and ranks content and presents precise information to users and also proactive information prompts to users who may not know what they need to seek. This type of service improves time to resolution, but what’s more, is it gives more insight into customer needs and a feedback loop to new products and services teams.

Sources:

http://www.computerworld.com/article/2982482/emerging-technology/why-artificial-intelligence-is-succeeding-then-and-now.html
https://community.dynamics.com/b/msftdynamicsblog/archive/2016/10/28/how-digital-transformation-is-impacting-sales-service-amp-marketing
http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html
https://en.wikipedia.org/wiki/Artificial_intelligence
https://www.wired.com/2016/12/artificial-intelligence-just-broke-steve-jobs-wall-secrecy/
http://www.economist.com/news/leaders/21650543-powerful-computers-will-reshape-humanitys-future-how-ensure-promise-outweighs




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