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AI and Automation in Sales and Marketing

There was a time, not too long ago, when applications of artificial intelligence were limited to the pages of science fiction novels. Yet, the concept of AI has been around for over 70 years now. Back then, we were still working to create a model of the most primordial component of AI: artificial neurons. For a long time after that, AI had slipped into the blind spot of the public eye, all the while growing smarter. It wasn’t until IBM’s Deep Blue beat Gary Kasparov in 1997 that AI stepped into the limelight and kicked-off the data race.

Today, of course, AI is a critical component of the digital imperative. The advantages of leveraging AI, in all shapes and sizes, have pushed businesses to invest heavily in its development and application. Operations in industries like transportation, entertainment, and manufacturing have witnessed terrific growth and outcomes as a result of AI adoption. Sales and marketing teams are no exception.

The ability of AI to automate sales and marketing tasks has shown great potential in reducing human effort and costs and bolstering top-line growth. AI technologies lower the time spent on administrative tasks, improve a brand’s ability to deliver personalized offerings to their customers, and open up previously unexplored revenue streams. This is why AI is at the core of the most promising initiatives in marketing automation.

According to the McKinsey State of AI in 2020 report, 79% of marketing and sales teams have witnessed year-on-year revenue growth thanks to AI adoption, and early adopters have reported greater customer satisfaction and up to 10% improvement of sales potential.

One of the most revolutionary AI-based technologies, at least for marketers, are bots. AI-based bots can perform certain human activities at a scale and speed beyond human capacity. Whether they are chatbots who can communicate, engage with, or troubleshoot customer concerns, or research bots that comb through terabytes of data to feed you critical competitor updates and data in real-time, bots are here to stay. That said, let’s take a deep dive into the bot ecosystem.

The Rise of the (Ro)Bots

Bots can be classified into two categories based on how they function. First, we have rule-based bots or pre-programmed bots. These bots rely on a dialog scheme that represents a decision tree where a conversation is prompted by logic jumps. In such cases, the interaction involves selecting from a limited list of preset options like “Why is my order late?” or “How soon will my order be ready?” This allows the bot to stick to a script. The other type of bot, the AI-enabled bot, is capable of conversing in loose dialog, which is dialog unguided by a script. These bots use natural language processing (NLP) and machine learning (ML) to analyze various aspects of the customer interaction such as intent, context, and complexity.

Chatbots have, during the course of the past decade, become a mainstay of the marketing framework. They have simplified the way businesses engage and re-engage customers stuck in the purchase funnel, reduced churn rate by analyzing buying pattern data and interaction preferences and providing personalized services, and enriched the post-sales journey.

The rise of AI-based chatbots has enabled businesses to communicate with their stakeholders without interfering with human-centric sales and marketing tasks. In alignment with today’s zeitgeist of highly personalized marketing, chatbots have introduced a new dimension of preference-based interactions. As a result, businesses are finding more reasons to deploy AI to automate prospecting, generate better leads, enhance researching capabilities, and improve customer experiences.

Dystopia or Utopia: The Debatable Future of AI in Sales and Marketing

Yes, bots have had a tremendous influence on the digitalization of modern sales and marketing frameworks. It is also more probable than not that bots will shape the future of personalized communications and impact purchase patterns. But there are pitfalls even to this growth.

In recent times, the proliferation of advanced malicious bots has become a pressing concern for businesses. This new race of bots is designed to attack infrastructure and incapacitate digital operations, extract sensitive information, and reduce overall productivity. What’s even more concerning is that 88% of organizations say that it is becoming increasingly difficult to detect these malicious bots.

Bots designed by humans to target vulnerabilities are one thing. But what happens when we reach a point where AI based bots have interactions with other AI bots with malicious intentions which can make bots learn to do what’s undesirable for the business? Given their learning models, bots may pick up unexplainable behavior that have a negative impact on organizational processes. Imagine another scenario where bots being used for selling goods online are interacting with the bots being used for procurement online. It would be interesting to see who wins or if it is a win-win situation.

But like all takes on good versus evil, it’s never simply black and white. In fact, many bots fall into the proverbial grey area—the questionable bots. These bots are good/bad depending on their business goals or simply on the situation and perspective. Social media bots, for instance, are good while automating social media campaigns and resharing relevant content. But they are bad when they disseminate malicious content and manipulate audiences.

Doing it Right

Inventions and innovations are focused at making lives better by offering positives. But, they may also cause disruptions and pitfalls unless enterprises design appropriate strategies to realise their full potentials. The same principle applies on AI and automation, which have immense promise. Their business benefits can only be optimised by astute planning, seamless implementation, and ultimately systemic delivery models. Bots will continue to influence and generate new business opportunities through multiple channels of communication, and the marketing and sales future of enterprises will be fast moving. The speed of doing business has to translate to the value generated, and AI and automation will expedite that pursuit.

In order to truly benefit from automation, sales and marketing teams must first standardise their own processes. This is a particularly important factor considering the blend of co-location and remote operations of the post-pandemic era. Once this is done, businesses will begin to see a measurable impact and lower costs related to data integration, technological deployment, and change management. But, businesses will need to opt for an implementation approach that is customised to the sales and marketing value chain. We may soon face a world where customers prefer talking to machines, because of their ability to offer instantaneous, empathetic, and value-added solutions.

Authored by:

Ravi Kathuria

SVP Marketing, Communications & Corporate Affairs , HCL Technologies Ltd.

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