Blog
Harnessing the Transformative Power of AI in CRM
- 06 September, 2023
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George Varghese, SVP, Consulting and Salesforce
George is the Senior Vice President of Consulting and Salesforce at Intelliswift, where he is responsible for spearheading the innovation and reinvention of Salesforce capabilities while enhancing our business consulting capabilities.
1. What is the potential of AI and what does the future entail?
Though AI is in its infancy, considering its potential & future we are already beginning to see a sliver of its tremendous influence in many significant spheres of life and very soon to be everywhere. Its course seems irreversible and if used with the right intent & vision, AI can be a great technology servant to humankind. Perhaps it is useful drawing an analogy as well as differences to earlier such technology waves that have heralded remarkable progress be it the printing press, industrial age, or the internet. All of them, in some form or the other, amplified our human capability to execute and process faster and better. However, they all required a person on the other side to decide, press a button or apply a creative thought.
AI takes it to a completely different level, and in a revolutionary manner, holds the promise to partner with us both in our ability to take decisions as well as apply creativity – and perhaps do it exceedingly better than us. When human supervision becomes redundant it is both exciting and frightening at the same time. Exciting, as it promises to make the worlds, we occupy a significantly better place and frightening because of its potential to make us irrelevant and replace our hold on the top of the food chain. If life took 3.7 billion years to become us in our potential today, AI with its infinitely faster processing and continuous learning, without the need to rest or sleep, could get to its maturity in a matter of years.
While AI till very recently focused on predictions based on existing data and was rule-based, the new Generative AI tools like ChatGPT utilize algorithms to generate new content— writing, images, video, or audio—from data that is provided which often includes the whole of the internet. This would mean larger outcomes that are unstructured, unpredictable, and creative. This has been mind-blowing and even more so considering that it is just the tip of the iceberg.
In the corporate world we are starting to see significant investments to use AI to automate processes, generate intelligent insights as well as create content anew to connect with customers and employees in ways that has never been done before.
2. What are the key trends and advancements in AI that is shaping Sales, Service & Marketing?
In an increasingly competitive business environment, where everyone is vying for the eye of the customer, delivering exceptional Customer Experience serves as the most significant competitive advantage and companies like Amazon have made this their primary mission.
Customer expectations of experience have significantly changed with the proliferation of technology and today 88% of customers say that “experience” is as important as the product/service itself. Customers expect speed in Sales & Service with 2/3 of customers saying that speed is as important as price. (Source: Time to Win). Most importantly customers expect to be recognized across all channels and wowed through hyper personalized experiences. This being the context, AI has been a trend setter delivering this promise while defining a new level of customer intimacy.
The benefits of leveraging enterprise AI products like Salesforce Einstein:
- Sales teams spend less time on non-sales activities and more quality time with customers as AI can automate a substantial number of sales operational tasks. As an example, Generative AI can create highly contextual automated client communication emails in seconds, a task that would have taken hours or days for a topnotch salesperson to create. It will also be an excellent assistant providing sales insights and focus areas. Organizations can quickly generate customer insights, pulling in relevant data from across the enterprise and outside getting a comprehensive 360-degree view of the customer, and then prioritizing leads, recommending up-sell and cross-sell opportunities, and forecasting sales for better context and quality in client communication and messaging. A McKinsey study suggests that a fifth of current sales team functions could be automated.
- Service teams can leverage AI to provide automation and 24/7 speedy contextual response to customer queries both through automated AI virtual assistants while also providing value-added quick knowledge support to human agents while servicing clients. Generative AI has taken the earlier rule-based approach to a new level by being able to increase call deflections by another 25%. It is also able to increase the operational efficiency of agents by automating tasks that are context driven and unstructured.
- Marketing teams can save on the enormous amount of time researching and creating segments by leveraging Generative AI to identify segments that may not have been evident in existing customer data. Without knowing all the details about such segments, they can then ask a Generative AI tool to draft automatically tailored content such as social media posts and landing pages. Once these have been refined and reviewed, the marketer can use gen AI to generate further content such as outreach templates for a matching sales campaign to reach prospects.
- Company leaders can get prioritized objective insight to drive quick strategy decisions based on Generative AI insights that also avoid bias and are based on data having to work through filters. A McKinsey study indicates that players that invest in AI are seeing a revenue uplift of 3 to 15 percent and a sales ROI uplift of 10 to 20 percent.
3. What are the challenges you foresee for Generative AI CRM and how are organizations like Salesforce addressing it?
Generative AI, with its hugely transformational potential has sparked the focus of every CEO who is looking for new levels of productivity, business models, customer experience, workforce tools and product strategy. All want the next generation AI capability, and it is their #1 priority, but there is also a wide trust gap that needs to be overcome. Per a Salesforce study, 59% of customers do not trust companies with their data.
How do enterprises ensure trusted productivity in AI insights, while issues of data privacy, hallucinations, data controls, bias and toxicity are addressed? In addition, the generic tools that are available like ChatGPT have not been purpose built for CRM which severely limits its usage & function at an enterprise level.
An AI system for an enterprise, leveraging the power of Generative AI, should consider the inherent structure of Large Learning Models (LLM) which form the foundation of Generative AI. The data that goes into the models must be filtered and masked to protect private and confidential information. Simultaneously, the generated output needs to incorporate toxicity detection, maintain an audit trail, and ensure zero retention within the LLM, all while operating within a client's trusted boundary. This is precisely the promise and commitment Salesforce Einstein delivers through their Trust GPT layer for customer data. Salesforce Einstein has been purpose built on the Salesforce platform as the first comprehensive AI for CRM.
The holy grail of a 360-degree customer view is often quite elusive. However, as enterprises prepare to use the power of Generative AI to transform customer experience it is most imperative to get the customer data together as organized, unified, and harmonized real time profiles leveraging customer data both from internal sales, service, marketing, and other enterprise systems as well as from external sources. Salesforce does this with a product called Data Cloud, a real-time Data Lakehouse built natively into the platform, that has the potential of bringing in billions of records with zero ETL copies while resolving identities by recognizing people across channels and devices.
Finally, one of the biggest challenges for an enterprise wanting to implement AI is to generate business value through identifying and prioritizing high value use-cases. This requires partnering with an organization that brings domain and technology expertise to inform the most relevant best practices.
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