Generative AI for Sales Management — Can You Automate Your Role?
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Generative AI for Sales Management — Can You Automate Your Role?
Real-World Experience Why Generative AI Is Not Your Silver Bullet (But Can Come Close)
On August 29, Eric Fraser (Culture Change Executive) joined me on “What’s the BUZZ?” and shared how he has been able to increase the level of automation in his sale management role — what roadblocks he has hit along the way. Sales managers find themselves awash in data, often spending countless hours on tasks such as data analysis and information sharing. While these activities are integral to a company's success, they frequently serve as roadblocks to more strategic pursuits. From automating repetitive processes to identifying unseen patterns in sales data, AI is proving to be an invaluable asset. However, its application is not without challenges. What are they and how can leaders address them? Here is what we’ve talked about…
When Numbers Meet Algorithms: AI In Sales Data Analysis
In the world of sales management, not every task is stimulating or fulfilling. Often, sales managers find themselves bogged down with data-crunching and information dissemination, jobs that are time-consuming but necessary. These tasks often require pulling numbers from various software, placing them in spreadsheets, and sharing them with relevant parties. While important, such repetitive duties hardly offer much joy. However, a silver lining exists in the form of Artificial Intelligence (AI). Though not with advanced conversational AI like ChatGPT or Bard, more traditional forms of AI can handle these tasks effectively. By leveraging AI, one can automate various elements of data management, thereby allowing sales managers to focus on more engaging aspects of their role.
Another significant area where AI shows its prowess is in pattern recognition within sales management. For instance, understanding the sales lifecycle involves recognizing broad patterns, such as needing to involve a CFO by a specific stage to avoid pricing issues later. Such patterns are crucial but may take time for a human to notice. AI, however, can identify these trends more quickly and may even uncover patterns previously unnoticed. It can sift through vast quantities of data to spot trends, thereby adding value to the sales process. Moreover, good quality data can amplify the effectiveness of AI in pattern recognition. It's like having an extra set of eyes that never get tired and can process information much faster than a human.
While AI can be extremely useful, it's essential to understand its limitations. For instance, AI might point out that in certain industries, sales approaches often only engage a single stakeholder in an organization, a phenomenon known as "single threading." Although AI can identify the issue, the 'how-to' aspect of addressing it still relies on human expertise and judgment. Currently, AI lacks the capability to provide actionable recommendations for how to resolve such specific challenges. Therefore, a collaborative approach between AI and human insight offers the best pathway forward. Leveraging AI for what it excels at—data analysis, pattern recognition, and task automation—while relying on human intuition for decision-making creates a balanced and effective strategy for sales management.
From Bad CRM Data To AI-Driven Insights
A common tool that sales teams use are Customer Relationship Management (CRM) systems that store information about prospects, leads, deals. But the data is only as good as what its users enter. Navigating the challenges of CRM systems often appears discouraging, especially when one confronts the discrepancies in data quality. This raises the concern of whether these systems provide an accurate representation of reality. However, the use of AI tools in data collection offers an unexpected solution. By incorporating AI into CRM systems, one can significantly enhance the fidelity of the data. With the aid of AI, it becomes easier to fill the data gaps and generate a more complete picture, thus offering a more promising outlook for users who initially feel discouraged by the quality of their CRM data.
» If you take certain AI tools and ask them to collect data, you can fill in the gaps of the picture in very surprising ways. So this is where, at first, I got discouraged early on. And then I got super encouraged when I just pushed the boundaries a little bit and asked the AI to do a little bit more. «
— Eric Fraser
Artificial Intelligence extends its influence far beyond mathematical equations and automated tasks. While it is often perceived merely as a tool to streamline workflows, its scope is much broader. AI offers unforeseen benefits, similar to innovations borne out of space exploration programs. At the onset, a discovery may appear insignificant, only to later transform entire industries. For instance, AI might initially save an hour on spreadsheet management but can eventually lead to groundbreaking developments in technology that impact numerous facets of life. Such ripple effects reaffirm that AI is not merely a tool for efficiency but a catalyst for innovation.
Ripple Effects When AI Meets Company Culture
The integration of Artificial Intelligence (AI) into a company isn't a straightforward task; it's a process filled with unexpected challenges, particularly regarding company culture. One key lesson learned from integrating AI into a smaller company was the underestimation of its impact on other departments outside the implementing team. The initial intention was to introduce AI to enhance the revenue team's efficiency. Contrary to expectations, teams outside the revenue department exhibited a heightened level of concern and, in some cases, alarm. This issue was manageable in a small setting but poses a significant risk in larger corporations where the ripple effect of such concerns could escalate. The takeaway? Effective communication is crucial. Without proper communication, employees tend to assume the worst, fearing job loss or negative impacts on their roles. Therefore, transparency about the AI integration process and its goals can alleviate fears and facilitate smoother transitions.
While the driving force behind AI implementation might be efficiency gains or cost reduction, companies must consider the human aspect. The aim might be to save significant amounts of money by reducing labor costs. However, creating a negative experience for employees can result in negative perceptions about the company. This could further affect their behavior and potentially nullify the intended cost-saving benefits. For instance, if the finance team becomes concerned because of poorly communicated AI initiatives, this could harm overall company morale and performance, thus erasing any monetary gains made through the use of AI. So, the objective should not solely focus on efficiency but also account for the employees' experience and well-being.
A disciplined approach can help identify the best areas for AI application within a company. Start by observing recurring questions or tasks that consume a significant amount of time. In a sales management context, one might often get asked about the most promising deals for the quarter. This recurring question could be a candidate for AI or automation, enabling a more accurate and time-efficient response. By paying attention to such patterns, employees can pinpoint tasks that could benefit from AI, improving not only their efficiency but also the quality of their work. Rather than hastily implementing AI, understanding the specific needs of the team ensures a more successful and smooth transition to AI-powered processes.
Summary
AI has the potential to transform sales management by automating mundane tasks and identifying crucial patterns in data. Traditional forms of AI can handle repetitive duties like data crunching, freeing sales managers to focus on more engaging responsibilities. AI excels in pattern recognition, helping to streamline sales processes. However, it has limitations and must work in tandem with human insight for best results. Additionally, AI’s impact goes beyond mere efficiency; it can act as a catalyst for broader innovation. Careful integration of AI is also necessary to mitigate concerns around company culture and employee well-being.
What are some unforeseen benefits of AI you have encountered?
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