Salman Shahid, CEO at OXO Packaging.
When it comes to leading sales teams, many tech founders fall to the common mistake of following outdated sales strategies. But adopting AI-powered sales strategies can be the answer to the sales woes of founders.
Here are four sales strategies powered by AI that you can adopt to strengthen the sales leadership framework of your organization.
1. AI-Powered Value-Based Selling Strategy
The value-based selling strategy is one of the pillars of any long-term sales pipeline for a company. This strategy depends on three factors: needs, challenges and goals.
Compared to common sales strategies that focus on the benefits and features of your products, the value-based strategy puts the wants and needs of prospects at the forefront. As the name suggests, this strategy aims to add value for potential customers that they won’t find elsewhere. This is how it helps you get closer to your leads.
AI can help tech founders better utilize the value-driven sales strategy. For example, if you have an IT company that sells complex software solutions and you want to create custom value propositions for all of your prospects, AI can help you fine-tune the value-based sales strategy in three ways:
• Audience Segmentation
• Competitive Analysis
• Compelling USPs
AI can help you obtain predictive analytics, such as industry-specific pain points of the customers. For example, you can use ChatGPT, Gemini or PowerBI to analyze consumer data. This data could reveal evolving consumer behavior to help you make tailored value propositions so you can make your product value-driven instead of being just “sales-y.”
With AI-powered marketing research tools, you can easily gather competitor data, which provides data-driven insights to predict future trends and refine your value-driven sales strategy in real time.
With consumer and competitor data, you can create unique selling propositions at scale to convert more SQLs faster than traditional sales approaches.
2. AI-Powered Lead-Generation Strategy
The goal of the lead-generation sales strategy is to get leads and nurture them through the sales funnel, converting them into repeat customers.
AI models like Microsoft Copilot make it easier for tech companies to efficiently and effectively implement lead-gen sales strategies that align with their measurable goals. Here are three ways AI can be used to improve the results of a lead generation strategy to boost sales:
• Content Marketing
• Seasonal Opportunities
• Influencer Marketing
AI-powered tools help make useful and engaging content using a customer-centric approach on all content marketing channels.
Tools such as ChatGPT create content for lead magnets, like e-books, free trials and discounts, to perform email marketing to boost sales and create personalized content after analyzing user behavior.
One of the best lead-gen strategies is to leverage trends and seasonal opportunities. For example, if you’re a product-based B2C tech startup, you can feed data from Google Trends to Gemini. Analyzing data this way will help you find trending Christmas gift ideas, so you can boost your sales during the holiday season.
Or you can speed up influencer marketing by using AI-data analysis tools to find relevant influencers easily and get more leads quickly.
3. AI-Powered Consulting Selling Strategy
The consulting sales strategy revolves around maintaining a good relationship between you and your prospect. You can implement this strategy by asking your prospects questions, analyzing their challenges and personalizing tech products/services that align with their needs.
Compared to the traditional sales strategies that are built on myths like “people always crave discounts” or “partnerships can boost sales,” the consulting sales strategy helps you position your brand as a trusted partner and allows you to win more sales without sounding “sales-y.”
For example, if you run a wearable fitness tracker startup, here’s how AI can be used to implement a consulting selling strategy:
• Crafting Personalized Pitches
• Developing Personalized Solutions
• Forecasting Sales Outcomes
AI tools such as Drift can create personalized messages based on the prospects’ needs. For example, if AI detects that the majority of customers are concerned about the cost, you will set prices accordingly while promoting the fitness tracker as a cost-effective solution.
Likewise, if AI detects that customers are more likely to buy products with personalized fitness plans due to some common health problems, it can offer the solution accordingly. You can modify the fitness tracker according to the prospects’ needs while making it cost-effective.
AI tools like Clari, Salesforce or Apollo help predict the sales generated by implementing tailored pitches and solutions. They can also predict any roadblock to achieving your sales targets.
4. AI-Powered SPIN Selling Strategy
The SPIN (situation, problem, implication, need pay-off) sales strategy is based on three factors: customers’ needs, effective communication and problem-solving. It revolves around asking questions to the prospects based on SPIN to ensure your tech product/service meets their needs.
Ask questions to understand the customer’s specific situation, problem or challenge. Then, inquire how your tech product or service can address their needs and help solve those problems.
Implementing a SPIN selling strategy becomes easier when you use AI. Here’s how the AI-powered SPIN sales strategy works:
• Analyze the situation.
• Identify the problem.
• Explore implications.
• Determine the need pay-off.
AI-powered customer data analysis tools such as Salesforce Einstein help analyze the customers’ current situation.
Let’s suppose that you’re the founder of an online ride-hailing service for tourists. The SPIN sales strategy powered by AI can be used to get more customers. For example, API access to Gemini models can be used for analyzing customers’ data based on their tour needs.
These models can also help identify the problems customers are facing during certain situations. It will highlight problems, such as long waiting times, which can have consequences like increased stress.
When the problems are identified, AI text models can make personalized pitches for customers addressing their situation, problem, implication and solution, which increases the chances of improved sales.
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