It wasn’t too long ago that artificial intelligence (AI) was associated with evil robots and vintage science fiction movies. Today, AI is fast becoming a fundamental component in human/machine and machine/machine interactions. AI and its companion technology, machine learning, are making devices and systems faster, smarter, more versatile, and more efficient. And both are poised to have a significant impact on sales and marketing.
Artificial intelligence is the ability of machines to make what might be considered cognitive decisions, similar to human decision-making, based on a variety of factors and influences. Machine learning, as inbound marketing consultancy Hubspot defines it, “is an application of AI and takes it a step further, allowing computers to continuously perfect those decisions, homing in on what works and letting go of what doesn’t.”
Both AI and machine learning are making rapid inroads into sales and marketing as business development shifts increasingly to digital, automated initiatives designed to make sales and marketing teams more efficient and productive. To achieve significant, sustainable growth through automation requires three key elements that include AI and machine learning:
High-quality Big Data that delivers sophisticated, accurate, in-depth information about current and potential customers.
Artificial intelligence tools that enable faster, more-informed decisions to be made about what to sell to whom based on that data, enabling sales and marketing teams to respond quickly and effectively to individual prospects at each stage of the sales journey.
Machine learning to enable the continuous refinement of automated customer relationship management (CRM) solutions. This will allow IT systems to play increasingly larger roles in routine (and even not-so-routine) processes, freeing sales and marketing professionals from repetitive, manual workflows so that they can focus on more important, strategic tasks.
Oracle is one company that is pioneering the use of AI and machine learning in sales and marketing. For example, the latest Oracle Customer Experience (CX) Cloud innovations enable sales teams to take advantage of data-enriched tools and recommendations to increase sales, improve customer satisfaction, and grow customer lifetime value in a digital, always-connected world where buyers are more knowledgeable and increasingly immune to generic, one-size-fits-all sales pitches.
A retail bank looking to increase sales throughout the customer lifecycle
Throughout its relationship with customers, a bank is constantly gathering information: gender, age, income, marital/family status, and assets, to name a few categories. The bank can use this data to inform its CRM system and determine the right products to market at the right time to individual customers – for example, mortgage products to potential homebuyers; education loans to parents with college-age children; and wealth management products to customers nearing retirement. Machine learning helps the CRM system evolve its response appropriately as each customer enters a new phase in the relationship.
A B2B enterprise needs to attract the most appropriate prospects and close more new business
Using inbound marketing to attract more prospects to its social media platforms and websites, companies can employ artificial intelligence to make sense of disparate information gathered from a variety of sources such as LinkedIn, discover.org, Hoover’s Online, social media channels and other digital sources. AI can turn all this data into valuable insights that can help sales teams direct their efforts to the most potentially lucrative prospects who are also a good fit for their firm.
Monitoring customer activity and engagement using AI tools enables the enterprise to accurately fulfill customer requests and perceived needs using automated solutions that “learn” how to respond based on the data provided through AI. Sales reps are then freed up to engage with customers more quickly and effectively as needed, creating positive customer experiences and longer-term relationships.
Platforms such as Oracle’s CX Cloud make it easy to integrate many data sources with your company and contact database, enriching it with additional data and real-time signals. AI can be used to predict or forecast outcomes using historical data, helping sales managers forecast their team’s performance for the quarter well in advance so they can take proactive steps to increase productivity based on the numbers.
The payoff of all this is increased revenue, reduced costs, and the ability to deliver an exceptional overall customer experience. It enables your company to deliver a highly personalized message at just the right moment throughout the entire customer lifecycle. For marketing, it’s making the right offer at the right time. For sales, it’s delivering value with every touch and offering the right solution for sales. And by automating previously manual workflows and helping systems “learn” how to respond appropriately to customers, it turns service people into proactive promoters for upselling opportunities.
The possibilities for utilizing AI and machine learning in sales and marketing are almost unlimited. New ways to engage with potential and current customers and improve their overall experience are being discovered every day. If you have not already done so, it’s time to embrace the future.
Jim Welch is a guest blogger about sales topics. Jim is a top-producing sales executive in the Customer Experience (think CRM) at Oracle with more than 20 years of experience maximizing sales opportunities within highly competitive markets. Jim has a proven record as both a team player and team leader. His experience spans large corporate and start-up organizations selling to commercial, state, local government and education clients.
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