May 2024
By Livio Moretti and Andrea Boeri
When Artificial Intelligence (AI) has just become part of almost everybody’s life, at least because it has been incorporated in many consumer products (even the once humble toothbrush), a new wave is coming with Generative Artificial Intelligence (GenAI). GenAI refers to algorithms (for example ChatGPT) that can be used to create new contents, such as code, images, text, audio, music, and videos, based on learned patterns and data inputs.
GenAI has the potential to impact a huge number of human activities. We focus here on a specific domain: GenAI potential to enhance the sales capabilities of B2B companies.
Eendigo is a global expert in value creation through commercial excellence, and we do not provide AI software solutions. Therefore, we believe to be well positioned to give a fair assessment about the role of GenAI in B2B sales.
B2B buyers would like to have a “B2C like” experience
First of all, does B2B selling require an innovative approach? The answer is a resounding yes. According to several surveys1, the “consumerization of B2B buying” has enormously progressed in the last few years. In other words, professional B2B buyers more and more expect to receive the same buying experience from their B2B vendors as they have as consumers when they use the main B2C e-commerce platforms, including personalized journeys, regardless of which channels they engage.
Here lies the catch: the gap between what buyers want and what most B2B organizations can deliver is apparently not narrowing fast enough. Buyers want omnichannel, readily available and up-to-date information, personalization, easy-to-use e-commerce and real “customer centricity”. Many B2B organization still struggle to deliver effectively, as they remain based on traditional, not data-driven sales approaches, or they are facing data scattered across a myriad of systems, like ERP, CRM, PDM, a lot of other acronyms and the ubiquitous spreadsheets.
Enhancing B2B sales with Generative AI
GenAI can enhance and reshape B2B sales in at least five ways.
Improved lead identification, targeting and segmenting
At the forefront of the funnel, GenAI outperforms traditional AI-driven methods for lead identification, targeting and segmenting prospects. GenAI can discern patterns within customer and market data, enabling precise segmentation and targeting of relevant audiences. Rather than investing time in manual research and segment creation, sales teams can leverage GenAI’s algorithms to uncover segments with distinctive traits that may have gone unnoticed. With a limited knowledge of these segments, they can prompt a GenAI tool to automatically generate tailored content, such as posts and landing pages.
Enhanced customer experience (CX) through personalized and data-driven outreach
Generative AI can analyze vast amounts of customer data, including past interactions, preferences, and industry trends, to craft personalized communication. This technology can generate tailored email messages, proposals, or product recommendations that are more likely to capture the attention of prospects. In addition, GenAI-powered chatbots are increasingly being used as virtual sales assistants. These chatbots can handle routine inquiries and provide product information.
Accelerated content creation
GenAI can assist in generating a range of content types, from blog posts to white papers, based on specified topics and keywords. This capability empowers sales teams to produce high-quality content at scale, establishing thought leadership and enhancing brand credibility2.
Improved salesforce productivity
GenAI can help sales teams to better prepare their interactions with customers and prospects3. It can also free up capacity to spend more time with customers and prospective customers. As the deal advances, GenAI can provide real-time negotiation assistance and predictive insights, drawn from comprehensive analyses of historical transactional data, customer behaviors, and other data.
Facilitated dynamic pricing strategies
Generative AI can contribute to dynamic pricing strategies by analyzing market demand, competitor pricing, and customer behavior. This technology can assist in setting optimal pricing structures in real-time, maximizing revenue while remaining competitive in the market.
Are sales teams ready for Generative AI?
Given its potential, you would expect sales leaders to have run to implement GenAI in their operations. Actually, according to an extensive survey run by GBK Collective4, sales leaders are curious but cautious, held back by several factors. Their main concerns5 were the accuracy of generative Al outputs (50%), followed by employee resistance (39%), ethical considerations (36%), industry compliance (35%), and other issues.
These concerns are certainly valid. Even if GenAI shows potential in translating buzz into B2B reality through a surge of innovation6 and, to some extent, hype, it’s crucial to exercise caution, especially in the short term. According to Forrester Research7, “thinly customized GenAI content could further deteriorate the purchasing experience for 70% of B2B buyers”. Despite its promising prospects, GenAI is still a technology in its developmental stages. While this technology undeniably holds transformative potential for B2B organizations in the long run, it will require time to reach that stage.
Current GenAI models have limitations that must be acknowledged. For instance, large language models may exhibit tendencies towards “hallucination,” providing answers that sound plausible but are untrue. Additionally, these models often lack transparency in their reasoning or the sources behind their responses. Consequently, companies should exercise extreme caution when integrating generative AI without human oversight, particularly in applications where errors can have detrimental consequences.
How to implement Generative AI
When organizations begin exploring Generative AI, they often overlook the operational challenges it brings. To mitigate this risk, according to Gartner it is advisable to consider a few key issues8.
- Launch one or more (but not many) pilots focused on demonstrating the business potential, rather than the technical feasibility.
- Be aware that identifying and prioritizing impactful generative GenAI use cases is going to be challenging, due to the broad and evolving nature of the technology (which leads to the need for a fast cycle of innovation).
- Adopt a fast and lean cycle of innovation (brief experiments to test how the technology could add value), aiming at developing the mimimum viable products required to test the use cases and refine the assumptions.Involve business partners (in our case, sales teams), software specialists and AI experts as key members of GenAI projects and pilot teams.
- Don’t hesitate to eliminate use cases that do not yield the anticipated business value.
Finally, there are some pre-requisites which need to be satisfied before undertaking a GenAI effort. First, embracing this path will require openness to change and acceptance of possible missteps and failures; a familiarity with agile methodologies will also help. Second, a consolidated digitalized, process and data-driven approach to sales should already exist. Last but certainly not least, a strong risk oversight will have to be in place: businesses must ensure transparency and accountability in AI-generated content to maintain trust and compliance with regulatory frameworks and protect data privacy.
Conclusion
In our opinion, the game-changing aspect lies not solely nor primarily in the tool (GenAI) but in the overall transformation journey leading to its full exploitation. This journey demands a clear vision and openness to change, a familiarity with data driven decision-making, well-structured sales processes, a strong cross-functional team play, investments in IT and the acquisitions of additional specific competences, a willingness to experiment patiently and accept failures along the way. Unfortunately, there are no shortcuts in this effort, but the size of the prize is usually worth it.
1 See for example: commercetools.com, “Pivotal Trends and Predictions in B2B Digital Commerce in 2024”
2 Google, “101 real-world gen AI use cases featured at Google Cloud Next ’24”
3 Nick Toman, Bryan Kurey, and Ray Makela, “What Salespeople Get Wrong About Using GenAI”, Harvard Business Review, December 7, 2023
4 GBK Collective, “Taking a Pulse on Generative AI”, October 2023
5 Jeremy Korst and Stefano Puntoni, “5 Ways Marketing and Sales Leaders Can Embrace GenAI”, Harvard Business Review, November 16, 2023
6 See for example: Financial Times, “OpenAI and Meta ready new AI models capable of ‘reasoning’”, April 9, 2024
7 Laura Ramos, “Predictions 2024: GenAI and Partners Help B2B Marketing, Sales, and Product Endure a Wild Ride Ahead”, Forrester Research, October 25, 2023
8 Gartner, “How to Pilot Generative AI”, July 10, 2023
Livio Moretti is the Founding Partner of Eendigo. Andrea Boeri is an Associate Partner of Eendigo in the Milan office