Targeting is one of marketing’s most effective strategies for engaging with customers. It’s a strategy that’s all about narrowing your focus to key audience segments and designing campaigns specifically tailored to them. Using data, marketers identify their most valuable customers and prospects – those who are most likely to buy what you’re selling – and the best ways to reach them. By zeroing in on their specific preferences and priorities – you can deliver more relevant, impactful campaigns that bring in more high-quality leads.
Done right, it enables better allocation of resources, builds deeper relationships with customers (B2C and B2B alike), and drives more revenue than broader, mass-messaging approaches. In email campaigns alone, marketers have noted as much as a 760% increase in revenue driven by targeted campaigns.
To understand your audience (and target them effectively), you need high-quality customer data. The better the data, the more valuable the insights you glean, and the more effective your campaigns become. Thankfully, there are AI-enabled solutions that can enhance your targeting strategy by equipping you with more accurate, high-quality data, so you can market with precision and confidence.
These days, we are swimming in data. We can keep track of every person involved in a deal, key details about our customers from industry to communication preferences and beyond. And all that information is extremely valuable. But, the sheer amount of it can be unwieldy to manage manually. That’s where AI comes in.
AI can process data much faster and more accurately than humans, especially at scale. Its automation and pattern recognition capabilities can unlock more effective campaigns that nurture buyers throughout the sales cycle.
Here are three ways AI helps improve the effectiveness of your campaigns:
Businesses look to CRM data to get a deep understanding of their buyers. Not just their basic contact information, but the role they play in decision making, and their impact on things like win rates and deal size. Traditionally, sales reps have had to enter all that information manually, an increasingly demanding task as buying groups get bigger and bigger. Considering that entering and assigning a single new lead takes an average of six minutes (three of which are spent just on the initial data entry), it’s not surprising that most sales reps don’t enter the details of every person involved in a given deal.
That’s why automation is critical. AI-enabled solutions automatically capture all the contacts and activities from every engagement – who was involved (both internally and externally), when they got pulled in, etc. Automating data capture can increase the number of contacts captured by 10-20x, and ensures the data is accurate. And when you have rich, accurate data around your deals, you can analyze it to gain meaningful insights.
2. Analyze Past Deals
Marketers use data from past deals to understand who their customers are – who are the decision makers, at what point do they buy in, what were their main questions or concerns, and so on. Issues arise when the data captured is inconsistent and incomplete. And even when the data is captured accurately, the sheer amount of it is a lot for companies to sift through.
AI technology can analyze data much faster and more accurately than people can. Not only that, it can detect patterns we wouldn’t, and surface them to the end user via visual dashboards. By compiling and standardizing all your data, you can look at key differences between the deals you’ve won and those you’ve lost. How many people were engaged in deals of a certain size? Which customer personas are involved in the high-value deals you win? That automated pattern recognition can help identify valuable trends and opportunities you may otherwise have missed.
For example, one company discovered that pulling IT into their deals at a certain point increased their chances of closing by 20%. Thanks to AI, something they wouldn’t have thought to look for became a key piece of their strategy.
3. Identify Core Buyer Personas
Personas are representations of your target audience segments used by marketing when designing campaigns and other engagements. They can be highly effective (90% of companies who use them get a clearer understanding of their buyers), but only if they’re based on real, quality data.
Typically, teams build personas based on past deals, market research, and customer interviews. But again, issues can arise when you rely on human data entry. Sales reps may enter things one way with one deal, but use a different taxonomy the next time. Enhancing the quality and completeness of your data will only make your personas stronger. AI solutions can analyze every contact involved in every deal in your CRM, so you get a more accurate idea of who the decision-makers and deal-breakers are and how to engage them.
Marketers use personas to understand what different groups care about – what their pain points and priorities are – so they can build content that’s relevant to them. For example, someone with the title Sales Director likely has different KPIs and challenges than someone with a VP or C-suite title). But job titles and roles vary company to company, making categorization exponentially more complicated. People.ai’s solutions use a proprietary taxonomy to automatically convert different titles into standardized roles. This saves a ton of valuable time and effort, especially when there are a lot of people involved in each deal.
Now that you have AI-enhanced personas and past-deal analysis informed by complete, high-quality data, it’s time to create and execute your targeted marketing campaigns and engagements.
This starts a virtuous cycle: effective targeting leads to higher levels of engagement, and each new engagement feeds back into the database, which is then used to inform your next engagement, and so on.
And even here, AI offers critical benefits when it comes to performance and attribution metrics.
One of the biggest blind spots marketers struggle with is knowing what happens to leads once they're passed over to sales. Imagine putting all this time and energy into building these campaigns, not having insight into the outcomes, and then being asked why your team isn't helping generate more pipeline for sales.
By monitoring engagement, you learn what about your campaign worked and what didn’t, so you can adjust your strategy next time.
Of course, everything we’ve discussed thus far is meaningless without clear understanding and alignment between Sales and Marketing on how it’s all going to come together.
For any targeting – enhanced with AI or not – to be effective, sales and marketing need to be aligned on their goals, strategies, and tactics. They need to work together to set priorities (Who are we targeting? At what point do we hand things off?) and execute their campaigns. Early alignment can lead to 3higher sales win rates, and make your company better at closing deals. But when your teams are equipped with accurate, high-quality data, it’s a lot easier to achieve the alignment you need. It removes the guesswork. You now know what has worked and where your teams should be focused. You have the proof.
Traditional targeting is like a roadmap, giving you a clear route to your customers. By enhancing that roadmap with AI, you turn it into a GPS. A powerful tool that can reduce guesswork, improve confidence, and let you market with adept precision. Targeted campaigns and communications, and all other go-to-market activities for that matter, are more effective when based on high-quality data, and AI is how you get there.
By embracing AI, you can get more personal with your customers, and build stronger human connections that drive greater lifetime value.