GPT for GTM: How AI Can Supercharge Your Sales Cycle

Generative Pre-trained Transformer (GPT) is a powerful AI model rapidly evolving the business landscape. Sales teams are leveraging this technology to gain a competitive advantage. 

It can potentially revolutionize various aspects of business operations. We will explore how GPT can enhance the sales cycle and supercharge your Go-To-Market (GTM) strategy. 

GPT: A Game-Changer for B2B Sales 

Each stage of the sales cycle presents challenges, which can take up a lot of time and resources, hindering sales effectiveness. 

Here’s how sales teams can apply GPT at different stages: 

1. Prospecting: 57% of sales representatives find prospecting challenging. GPT helps qualify leads by generating a list of prospects by training the language model on ideal customer profiles, historical lead data, or industry-specific data. Sales teams can prioritize promising leads by analyzing and scoring leads with the model. 
2. Outreach and engagement: GPT can create targeted outreach messages. With the right inputs, the model can write personalized emails and messages resonating with the prospects. It can offer talking points on your draft emails, boosting response rates. 
3. Conversion and discovery: GPT can assist salespeople in real-time during discovery or sales calls. The model can listen and suggest questions, objections, or product information to help the salesperson. GPT can be a “virtual sales assistant” by improving the salesperson’s knowledge and interaction. 
4. Proposal generation: GPT can create customized proposals with relevant inputs like customer requirements, pricing options, and value propositions, saving salespeople time and delivering professional proposals to prospects. 
5. Sales enablement and training: GPT provides sales enablement training materials. The language model generates sales playbooks, objection-handling guides, competitive intelligence, and product training modules to help the sales teams learn the required skills. 
6. Customer support and upselling: GPT can help customer support teams resolve issues quickly and accurately by training the model on customer data and support knowledge bases. It can recommend cross-selling or upselling opportunities based on customer history and preferences. 

How B2B Sales & Marketing Teams Can Leverage GPT 

Here are some specific ways GPT can help sales and marketing throughout a customer’s buying journey.

1. Create content and email marketing campaigns

Sales teams can leverage GPT to create personalized blog posts, whitepapers, case studies, and social media posts. They can train the GPT with relevant data and provide specific instructions to attract B2B customers organically. 

GPT enables sales teams to customize email templates, subject lines, and body content and recommend language and messaging that engages and converts prospects.

2. Qualify leads and schedule demos

Lead qualification is like panning for gold: tedious, time-consuming, and inefficient. Until now! 

GPTs ML algorithms analyze massive amounts of data and predict how to process them based on past successes. 

Salespeople can engage with customers earlier in the sales process, from gathering potential interests and needs to answering customer inquiries thoroughly. 

After finding potential prospects, Schedule demos to educate and convert them. 

GPT searches your sales funnel for leads likely to want a demo based on previous experience and predetermined parameters so the salesperson can focus on convincing other leads.

3. Derive competitive intelligence

Using GPT, B2B sales and marketing teams can collect and analyze competitive intelligence. GPT can provide insight into competitors’ strategies, product positioning, and market trends by training the model on data specific to the industry. 

This data can assist teams in refining their strategy and differentiating themselves in the market.

4. Build customer trust and increase their satisfaction

GPT analyzes customer interactions and spots suspicious behavior before it becomes a problem. AI can detect early signs before customer distrust happens. 

It can help businesses improve trustworthiness, transparency, security, and user experience to give customers confidence in their services. 

With GPT, customers will get more accurate responses from salespeople and feel like they’re getting personalized attention, which can be hard with cold calls and emails. 

This tool helps sales teams exceed customer expectations. Satisfied customers benefit everyone! 

GPT in Action 

Despite the recent adoption of GPT, 47% of sales executives believe that AI can improve sales performance. Here are examples of companies getting in the GPT action. 

1. Microsoft’s Viva Sales suggests email content for inquiries or proposals, including pricing and deadlines, saving time for sales teams to build relationships. Sellers can edit and send automated responses. It combines data from Microsoft Graph and CRM to deliver a better customer experience. 
2. Adobe uses GPT to create personalized marketing campaigns. Adobe’s large language models integrate with Microsoft’s Azure OpenAI Service to help users create advertising emails, text copy, and web pages. The models will caption Customer Journey Analytics visualizations. 
3. Morgan Stanley’s internal chatbot searches wealth management content using OpenAI’s GPT-4 embedding and retrieval capability. Advisors can instantly access top experts like the Chief Investment Strategist and Global Equities Strategist with this transformative capability. Morgan Stanley is exploring OpenAI to improve advisor notes and client communications to improve client service. 

AI will enable more complex applications, and GPT models can be trained on massive sales data to produce accurate sales forecasts and predictive insights. 

Sales intelligence tools like Draup for Sales can provide buyer information before competitors can. You can: 

• Filter insights by deal size influence, budget control, personality traits, sales engagement guidelines, etc. 
• Hyper-target prospects by location, funding status, company size, leadership changes, etc. 
• Target prospects with alerts on key signals and build detailed target prospect profiles. 
• Generate B2B leads with ML-based recommendation engines.