The rise of artificial intelligence (AI) is a story that reads like a modern-day saga—a journey that started off in the imagination of futurists until its impact was heard echoing across the world, seemingly arriving overnight, transforming our understanding of what AI was about to unleash on the world. Although most people are just beginning to comprehend the implications of AI in the last year or two, AI represents a great culmination of human ingenuity stretching back for decades. The most prominent iteration of artificial intelligence we’re familiar today with comes in the form of so-called “large language models” (LLM’s). As the name might suggest, the language models have been trained to mimic human language and operate in text-based responses -or, something a human can understand better than binary code. At first, these models were rather crude and limited, but over time, and with enough training and data, they began to reach a point where it became increasingly difficult to tell whether you’re interacting with a human, or an algorithm. This introductory description of AI is very basic, and barely scratches the surface of what AI is, or what it is capable of. Also, just like the rise of the internet, there were many aspects of AI we probably haven’t even comprehended, and although LLM’s represent our first big adoption of AI, how this trend evolves from here remains yet to be seen.
To get to terms with AI’s transformative potential, let’s take the story of ChatGPT— a story you are most likely familiar with. The emergence of ChatGPT onto the world stage brought AI out of the shadows and into the global spotlight almost instantaneously. ChatGPT demonstrated with startling clarity its capabilities for practically anyone with a smartphone and internet connection and, AI, no longer just a sub-genre of sci-fi movies, became a real-world application overnight. It was reported to have attracted over 100 million monthly active users within two months of launching, making it the fastest-growing consumer application in history. Humanity had its first real taste of what AI offers, and, without a doubt, this potential was realized by the commercial sector. In unison, the business sector entered an AI race, investigating ways in which AI could introduce intelligent automation, predictive insights, and craft personalized experiences, and more.
The ChatGPT phenomenon wasn't just a technological breakthrough alone; it was more like a paradigm shift. You see, although there were indeed previous iterations of “chatbots” before ChatGPT, they were mostly flimsy and clunky in their understanding and ability to respond to unique input. Anyone who’s ever visited a website with a chatbot trying to answer your questions when all you want to do is talk to someone knows this well. When ChatGPT hit the globe, it's uncanny and seemingly intelligent responses to almost any question changed the old perception of dull chatbots, and the idea of conversing with a machine in a natural, human-like way became reality.
Although AI wasn’t a new topic, it could easily be argued that the launch of ChatGPT marked the moment artificial intelligence reached escape velocity and brought a collective understanding around the globe that AI wasn't just an imaginary tool for the future, but an immediate and tangible tool that could be harnessed immediately. Pandoras box had been opened, and companies around the world were discussing AI’s potential in all areas of business, from marketing, sales and tech.
Off the bat, most people saw ChatGPT doing things such as coming up with article titles, writing lyrics to a song or suggesting recipes. However, it’s potential began to explode far beyond its initial use. Soon, it was writing code and predicting stock markets, and users started pushing ChatGPT to its limits and test its ability to perform more complex tasks. It ushered in an era where algorithms could decipher complex instructions, easily perform repetitive actions with minimal input, and provide insights into data that we couldn’t see before. Thus, AI's reach spread like wildfire, making its way into every nook & cranny of industry, from IT, finance, manufacturing and more.
In this chapter, we journey beyond the surface, delving deeper into the profound impact AI has on the realms of sales, marketing, and revenue operations. As we explore this topic, it will become apparent that AI's potential, while indeed fantastic, are fundamentally rooted in the quality of the fuel that powers it—data. As we advance through the series, we will unpack the binding link between AI’s ability and the quality of the data it has been fed. This dynamic symbiosis is what holds the key to unlocking AI's potential for your business.
Sales: Imagine your business instantly had the cheat-codes that empowered all your sales teams to operate with a heightened sense of precision and foresight. Well, that’s exactly what businesses around the world are exploring right now. But how? One great power artificial intelligence has introduced is the ability to add value into decision making processes in sales. Data-driven insights and actions are becoming increasingly valuable to organizations as they can handle and process data automatically, as well as reveal hidden gaps and suggestions for improvements.
Using AI, new leads can be evaluated not only based on surface-level information, such as a job title, but also on a nuanced analysis of historical data associated with the email domain, specific department, company interactions, open opportunities and more. Or it’s possible to use an AI-powered lead scoring system that automatically ranks your leads without needing you to lift a finger.
Think that’s cool? Check out the new “Ask ChatGPT” function from Plauti’s Data Action Platform (DAP). Now you can easily make use of ChatGPT’s powerful language processing abilities to assign incoming cases in your Salesforce org to the right department based on information in specified fields.
By using predictive analytics, AI can assign values to incoming leads based on conversion likelihood. It can do this by examining a range of data points, including past interactions, purchase history, and engagement patterns. These AI powered insights provide sales teams with valuable info, as well as a blueprint for prioritizing their efforts in the most effective way. The result? A more efficient allocation of resources and higher conversion rates from helping sales teams to focus their energy on leads with the highest potential.
Additionally, AI revolutionizes sales forecasting by analyzing historical sales data, market trends, and yet-unidentified external factors that could possibly influence purchasing behavior's. Again, the results are clear; forecasts that were once missing the target became more accurate and actionable. Also, since AI can work with incoming data faster than any human, insights can adapt in a more dynamic fashion to changing market conditions.
Marketing: The evolution of marketing has been enormously impacted by the rise of AI. For starters, AI's ability to comprehend, process, and respond to massive datasets is already a jaw dropping feature that opens new avenues for any adventurous marketers. For the marketing world, AI is their key to an all-seeing eye of customer information, capable of sorting through millions of data points effortlessly to uncover new trends, behaviors, and preferences that influence customer interactions.
In the modern world of marketing, personalization is now expected as the norm, and AI takes personalization to new heights. AI can inspect customer data and use this information to craft personalized; relevant messages tailored to an individual preferences. This new wave of dynamic content creation makes it much easier for companies to create a more personalized experience for each customer. When customers feel this way, the result is always the same; better engagement and brand loyalty.
Predictive marketing analysis is another avenue where AI has entered the marketing world. By leveraging historical data, AI models can predict the chance of success for marketing campaigns and allowing marketers to fine-tune strategies to perfection. This efficient approach and lack of guesswork means budgets can be better optimized and foster a higher ROI.
RevOps: It should come as no surprise that revenue operations have felt the impact of AI in one way or another. For revenue operations, AI emerges as a magnetic force that unifies the multiple data sources they work with and enhances decision-making by seeing the bigger picture in the data. In this regard, AI is the apex data cruncher, and its ability to work with various sets of data allows it to bundle information from disparate data streams into a unified and single pane view.
Ask any revenue operations team and they will tell you that an important metric they care about is churn rate. AI-driven churn prediction comes in as a lifesaver and fortifies revenue operations with its ability to analyse historical customer data and reveal valuable points of interest. For instance, AI is unmatched in its power to identify patterns that often proceed churn, giving a businesses the power to proactively address any customer concerns before they lead to negative consequences, such as cancelling a contract or subscription.
Additionally, we can already see how quickly AI changing RevOps by taking over tasks that we usually heavily dependent on manual labour. AI excels in its ease to initiate automatic tasks that are mundane, and this liberation from repetitive tasks means freeing up time for more important things. With reliable, automated processes in place, revenue operations professionals can then redirect their focus toward tasks that require their additional care or immediate attention, such as manually reviewing potential issues that AI flagged for inspection.
As we venture further into the relationship between AI's potential and the quality of data it builds itself upon, a foundational truth emerges into plain sight—a truth that is found in the power of clean CRM data.
If AI is a conductor leading a symphony of insights, then data is the meticulously prepared score which it plays according to. AI derives insights, predictions, and recommendations from the quality of its data source. In music, a single error on the score, even a misplaced note, can break the harmony altogether. In the same way, a single point of poor data can have a rippling effect that can impact the flow and outcomes of your business.
If we consider AI's predictive abilities within sales, or imagine AI algorithms analyzing customer interactions, purchase history, and preferences to forecast potential buying behavior, we soon realize the ramifications of errors in the data could be huge. This prediction, however, is not an isolated event—it's a product of the quality of data on which AI's intelligence is built. Clean CRM data ensures that patterns and signals aren't muffled by noise, allowing AI to deliver forecasts that are not only accurate but also actionable.
In the realm of marketing, AI's prowess in personalization is amplified by clean data. AI crafts tailored messages, product recommendations, and content based on individual customer behaviors. This level of personalization isn't speculative—it's rooted in clean CRM data that captures the nuances of each interaction, fostering engagement that transcends the ordinary.
Furthermore, within revenue operations, AI's role as a data unifier takes center stage. Unified data sources, cleansed of duplications and inconsistencies, empower revenue operations teams with a holistic view of customer interactions. This panoramic perspective underpins strategic decisions, enabling revenue operations professionals to navigate with clarity and foresight.
Like the path of any technology, AI's evolution is also an ongoing journey. As AI gains more headway in CRM usage, clean CRM data will act as both a catalyst and a stabilizer. Data deduplication, a keystone process in data quality management, exemplifies the close relationship between AI's reliability and trustworthiness vs the quality of its fuel. Just as a skyscraper requires a solid foundation to support its weight, AI requires a reliable data foundation to support its use. Data deduplication is like the concrete in the foundation, providing a reliable record of truth that allows AI to carry out its tasks without hitting roadblocks. Beyond just scalability, data deduplication should be a part of any company's goals path towards overall data hygiene. It’s really the elementary way for any organization to begin to up its data hygiene score. If your business is looking to explore the potential of AI further, such as inside Salesforce, this point couldn’t be stressed enough. If there’s one thing we know, it’s that inaccuracies and duplications will severely impede AI's ability to perform at its highest level. If there’s a final point for this chapter, it would be that clean CRM data is the guiding light that illuminates AI's path to excellence. In the following chapters, we'll explore the mechanics of achieving clean CRM data and unravel the nuances of its pivotal role in AI's transformative journey.