AI for Sales Prospecting: Common Use Cases and Helpful Tools

If only I had a dollar for every LinkedIn post about how AI is revolutionizing sales! I would be chilling on my very own yacht somewhere in the Mediterranean 😉

Sadly, I’m nowhere near the Med, yet the amount of content exploring the ways sales teams can leverage AI is really impressive. And, considering the reaction to that content, the number of people looking to jump on this bandwagon keeps growing.

An avid tech user and automation enthusiast, I couldn’t be more excited about where the industry is headed. Especially in the areas that have been slow to innovate, like prospecting. Arguably the hardest part of the sales process, it could really use some help!

Let’s talk about how you can use AI for prospecting in more detail (along with the tools revolutionizing the process).

Prospecting challenges that AI can solve

When it comes to prospecting, SDRs face a lot of challenges. They have to know exactly WHO to reach out to, WHEN, and HOW. Plus, they should find a way to do so efficiently – with minimum time and effort. So AI to the rescue!

• Data quality – The key prospecting challenge most SDRs face is outdated or simply limited prospect data (that also often comes at a pretty steep price).  AI can help SDRs build laser-focused prospect lists and engage the right people by easily sourcing the right data around the web and automatically verifying or enriching it in your CRM.
• Timing – Another problem here is the ability to reach the prospect when they are ready to buy (or at least show some interest). AI helps SDRs spot various buying signals and define the right moment to contact each prospect based on their intent or other activity in real-time.
• Targeting – Similarly, SDRs often struggle to make sure their outreach is relevant and hits the right spot. AI can help them qualify the prospects, whether it’s through more precise ICP or based on each prospect’s recent activity.
• Productivity – Lead research alone consumes about 21% of a B2B sales rep’s time, according to Salesforce. AI can take care of the manual work to help SDRs prospect more efficiently.

Of course, these are only the most common prospecting problems AI can help you solve. The list can go on. Now, let’s break down the practical AI use cases in prospecting and the tools you can use to implement them.

5 ways to use AI for sales prospecting (+ useful tools)

I bet you’ve already tried using generative AI tools to write or improve your cold email templates. But this is just one of the ways to use tools like ChatGPT in sales development. 

Prospecting – the initial stage of the sales process where you proactively identify and discover potential customers – has been relatively slow to get its AI level up. Which is a huge oversight because there are a ton of opportunities here (as mentioned above).

Let’s explore some of the potential ways to use AI for sales prospecting, along with the tools that can help you do that.

1. Data cleaning and enrichment

Data management – from sourcing and enriching the contacts to organizing and categorizing this info for your convenience – is the first use case for AI-powered prospecting. Unlike traditional automation that allows you to do similar tasks at scale, AI adds a layer of intelligence to the process.

For example, Rows (by far my favorite no-code spreadsheet tool) integrates with ChatGPT so you can turn the prompts into functions to clean up company names, generate short company descriptions, pull any additional info (like specific integrations, company values, custom hooks, etc.) in bulk to add to your prospect list and use later in your outreach. You can even use it to translate your greetings or P.S. text to each prospect’s native language (a cold outreach hack I’ve been using for a while).

One more great tool in this category, Double is specifically designed to help you “clean, enrich and qualify leads” with AI. There are tons of automations you can use to find LinkedIn profiles by name (or company website by company name), scrape them, clean up names and phone numbers, categorize companies by industry, etc. With 500 free credits/month, it’s a great tool to play around with while you’re only testing the waters with AI prospecting.

If you’re focusing on startups, Harmonic might be the perfect source of data for you. It uses AI to keep track of the fast-paced startup market, sending timely updates on recent activity or news so you can enrich your prospect lists. There’s also an AI-powered relevance scoring option to fine-tune your search.

2. Account-based prospecting

Let’s move on to the next potential area of application for AI in prospecting and talk about how it can help you spot the right people to target. Account-based prospecting is a perfect use case here. Also referred to as “precision prospecting,” it allows you to target the right people based on your ICP.

Simply put, you can train an algorithm to find the “lookalikes” of your ideal customers. This is exactly what Ocean.io promises. With context-based company search, you can target niche industries and find the perfect accounts to target with your sales efforts. It will also update and optimize the search criteria as you close new deals to keep your pipeline full of prequalified leads.

Looti takes a similar approach, scouring through your CRM to cluster the available data and identify your perfect customers. It will pick the right attributes to help you target your best audience for account-based prospecting. 

One more promising tool in this category is LoneScale. It promises to boost your team’s efficiency by delivering sales-qualified leads – people that perfectly match your buyer personas – along with additional information for each account, including relevant pain points and intent signals. The latter brings us to the next AI use case in prospecting.

3. Intent-based prospecting

This is easily my favorite prospecting approach. I see a huge potential in “warm outreach” where you use various intent signals to identify and engage the right people at the right time (as opposed to reaching out to complete strangers out of the blue). And it becomes so much easier and more effective with AI!

An interesting tool here, Lift AI provides real-time buyer intent data so you can pinpoint and engage the prospects who are most likely to convert. Using machine learning, it identifies and scores the promising prospects so you can further act upon each visitor and engage them using ABM, content personalization, retargeting, or other tools.

Triggr stands out in this category, by constantly crawling the web for any relevant events and sending real-time notifications to your team as they occur. This might be any activity related to funding, technology installs, hiring, news mentions, etc. As a result, your SDRs can act on those signals instantly, increasing their chance for success.

Tracking job changes of your past/current prospects is one more way to get a few more leads every month (especially if you’re targeting a fast-paced industry where people quickly switch roles or companies). This is exactly what Bluebirds AI can help with. It uses machine learning to identify champions across the current accounts in your pipeline and detect their job changes automatically. As a result, you can continue selling to those warm leads at their new companies.

4. Intelligent lead scoring

This use case is somewhat related to the previous ones but still deserves an honorable mention. I’m talking about AI-based lead scoring and qualification for more targeted, accurate prospecting. This can be a huge time-saver for SDRs and a great way to focus their efforts on the most promising opportunities rather than chase cold leads.

One of the most promising tools in this category is Oppwiser. It doesn’t just provide targeted prospects based on certain signals but also scores them to keep you focused on the most promising ones. The tool can also help you spot dormant opportunities in your CRM as well as notify you about new in-market accounts that match your criteria. What’s more, Oppwiser will send you daily “Next Best Buyer recommendations” for more effective engagement.

If you’re looking to get the most value out of your website visitors, Tomi.ai might be another tool to consider. Its predictive AI-based scoring algorithm identifies your website visitors’ behavioral patterns to predict the purchase value of the new ones (even if they are anonymous). As a result, you can target prospects based on their potential value for your business, not just the ICP criteria.

A slightly more sophisticated tool, Forwrd allows you to build “predictive AI apps” for many use cases, including account and lead scoring. You can integrate it with your CRM or any tool (or data source) for multidimensional scoring based on your users’ journeys. Most importantly, it works in real-time to offer instant insights into your best accounts.

5. ICP refinement and targeting

Last but definitely not least, targeting and ICP refinement is one more way to use AI for prospecting. This is often achieved through customer profiling – analyzing the available data about your closed deals or current prospects in your pipeline. This can be anything from account details to conversational intelligence insights from your sales calls. The latter may even include some personality traits. 

Probably the most popular tool in this category is Crystal. While it’s been on the market for a while, I still haven’t met any reps actually using it, so maybe the current AI trend will help them ramp up! It positions itself as a personality data platform, helping sales teams better understand their buyers and tailor their communication strategies accordingly. The personality insights can be collected as you browse the prospect’s LinkedIn profile or during the calls. 

As a result, this allows you to add psychographics and behavioral insights to your ideal customer profile. Crystal also helps you segment your lists as well as route the prospects to the best-fit SDRs. Their writing assistant will then help you adjust your pitch – the wording, style, and tone – so it resonates with each prospect.  

Another up-and-coming personality analysis software is Humantic AI. While it’s typically listed as a personalization tool, its buyer intelligence aspect can offer valuable personality insights. The software will analyze your past won/lost deals and engagement activity to finetune ICP & buyer personas.

The rise of the AI-powered SDR

Watching the key tech trends in sales and sales development over the past few years, I predicted that AI would go mainstream in 2023. By now, all SDRs I know have at least a couple of AI tools on their stack. 

Moreover, we see more of the sales tech industry players adding an extra layer of intelligence to their automations or even pivoting their products completely to prioritize AI capabilities (just like we did earlier this year with Jason AI). This means that the SDR tools stack evolution will continue bringing more opportunities and power to those who keep up with the trend.

According to McKinsey, 90% of commercial leaders expect to use generative AI solutions “often” over the next 2 years with over 20% of digital budgets already invested in AI-related technologies. But, as the researchers mention, the current use cases for AI in sales barely scratch the surface of what’s possible.

So it’s safe to say that we’re yet to see the rise of the truly AI-powered SDR.