How AI and Bots Will Address the Need for Speed in 2022

How AI and Bots Will Address the Need for Speed in 2022

Now more than ever, time compression is everywhere. Popular online “speed-to-serve” masters such as Amazon and Uber have conditioned us that we should never have to wait. Today, speed is a critical customer experience issue.

Responding to a lead must be done in seconds or minutes and you should highly accelerate the Service Level Agreement (SLA) completion time. Replying to customer support questions must be fulfilled at unprecedented speed to prevent wait times that evolve into poor reviews.

Organizational models and technologies need to evolve to increase speed-to-serve expectations. Sales, marketing, and service need to operate as one team, with hand-offs in seconds and back-and-forth responses in minutes. Data must be shared, and data-driven processes, priorities, next steps, and outlooks automated via AI.

Bots will become the front line for “hyper-convenient” engagement as a first step before getting routed to a human in sales, marketing, and service. Bots will handle tedious tasks and increasingly offload significant amounts of manual, repetitive work, freeing humans to focus on more inspired, value-added work while meeting the need for speed in 2022.

2022: The Year AI Breaks Through the “Human Trust” Barrier

Marketers don’t trust AI yet—2022 is the year that they will.

Companies are still cautious about relying on AI to analyze and automate business processes, so they work in a “dual-mode” of people and AI until they feel confident in the AI skills. 2022 is the year when AI will prove its mettle by offering near-term guidance, assisting sales and marketing with recommendations that they can choose to follow, and, over time, as AI proves to be accurate and helpful, trust is established.

AI used to analyze and automate business processes

In 2022, top areas for the application of AI for sales-marketing-service include:

  • Lead quality analysis—i.e., the likelihood of converting and closing
  • Nurture campaign effectiveness—i.e., attribution and adjustment
  • Probability of a lead converting, probability of a lead closing
  • Churn analysis
  • Forecasting and pipeline analysis
  • Sentiment analysis for case handling, sales engagements, and next best actions
  • Next best actions overall
  • Anomaly detection—i.e., analyzing data to find the “interesting” bit that needs attention
  • Conversational AI-powered by bots—for anything from marketing engagements, sales qualification, and customer support

As AI helps organizations make better decisions and reduce blind spots, busy work, and roadblocks, AI in sales, marketing, and service will become more trusted.

Companies aim for one common customer data platform that leverages AI-driven insights to manage data volume, analyze past, present, and potential future issues, and become proactive by responding to customers’ problems before they realize they have them.

Rich Green
Rich Green Rich Green leads SugarCRM’s engineering and product management teams and is responsible for the product vision and global strategy of the award-winning Sugar platform. Rich has more than 25 years of technology experience and has demonstrated success as part of both Fortune 500 and early-stage companies. He joined Sun Microsystems in 1989 where he held a variety of roles, ultimately serving as Executive Vice President of Software. As EVP of Software, he was responsible for Sun’s software products strategy and development, including the acquisition of MySQL, and driving Sun’s product, licensing and support businesses. His tenure also included roles as VP/GM of Solaris and Java, during which he led the invention, marketing and licensing of the enterprise and mobile versions of Java and was responsible for the release of Java as open source technology. After Sun, Green served as CTO of Nokia and Executive Vice President of the consumer and enterprise business at Nuance Communications. He most recently led Products and Technology at an early-stage Internet of Things company bringing connected sensors and data analytics to commercial-scale energy control.

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