If you could pinpoint the exact prospects and accounts in the market for your needs and then target them with messaging tailored to their specific buying stage, challenges, and interests— wouldn’t that be great?
As marketers struggle to reach and resonate with the right audiences in a sea of competitive noise, intent data— data that identifies exactly when someone is in-market or considering a specific solution— provides an accurate and effective solution.
Let’s use virtual reality (VR) software as an example to better understand data intent. Imagine your creative team has decided to use virtual reality to improve their digital customer engagement strategy. Initially, a few people from your company, most likely the creative director or a 3D engineer, will look for the VR software they require.
They’d most likely start by using a search engine, which would lead them to an e-commerce site or an article. After a few hours, they’ll probably realize that they’d spent all their time searching through countless VR software offers.
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They may do this several times over the course of several weeks or months as they determine exactly what software they need to acquire, the appropriate types of content they want to create, and the best strategy to implement.
That’s fantastic, but what does it have to do with intent data?
The more someone searches for a specific topic or area, the more likely it is that this person is seriously interested in purchasing. Furthermore, if you know someone is interested, you can specifically target them and persuade them to purchase the product or service from you.
In this article, we’ll discuss the different types of intent data and how you can use intent data to leverage your sales growth.
Different Types of Intent Data
There are four major types of intent data you need to be aware of. Each type provides a different level of insight into buyer behavior, so it’s critical to understand the distinctions between them.
1. Internal Intent Data (First-party Data)
This type of data comes directly from your audience and customers, and it’s widely regarded as the most valuable. Not only that, but it’s also free, making it the most cost-effective.
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The first party data includes information gleaned from interests displayed on your website(s) or app(s), data stored in your CRM, or social information.
2. Second-party Intent Data
This is essentially someone else’s first-party data. The seller collects data directly from their audience, and it all comes from one source.
Imagine you’re working with a business analytics firm to organize a webinar on big data analytics software usage. While you’re collecting registrations, your business partner will want to know who registered for the webinar so that they can interact with them in the future.
Second party data transactions are also very transparent because you work directly with a company. You have control over what you buy, the sales terms, and how the information is used.
3. External Data (Third-party Data)
Third-party sources collect this type of data (usually via cookies and at the IP level), allowing you to gain insight into intent on sites other than your own.
This provides you with a more complete picture of an account’s online interests and intent, and the ability to highlight intent on specific topics and sites relevant to the focus of your campaign.
When first-party and third-party intent insights are combined, they can provide a comprehensive picture of what an account is looking into, their business goals, drivers, challenges, and, most importantly, their likelihood to buy.
4. Search Intent Data
When someone enters a keyword or phrase into a search engine, search intent data is collected (e.g., Google, Bing). You can use this data to identify the types of queries your target audience is looking for and provide the most relevant answers.
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For instance, imagine you run a customer satisfaction (CSAT) consulting service, you may discover that your target audience is looking for “How to do an effective CSAT calculation?” You can use this information to create content that meets the needs of your target audience.
How Can Intent Data Be Used to Increase Sales?
1. Product development and competition elimination
Companies seek intent data in order to understand user needs and then develop products to meet those needs. After understanding these needs, the company can create products based on them to entice users to buy the products.
Imagine you run an e-commerce store. With sufficient intent data, your marketing team can discover and propose solutions to your users’ needs based on patterns and similarities that influence future ecommerce trends, actions, and behavior, allowing you to acquire more customers by converting those who are not loyal to competitors.
2. It enables more precise and targeted personalization
For today’s marketer, personalization is key. By using intent data, you can remove the guesswork from marketing and deliver content based on user browsing behavior.
Brands that truly understand customer intent— what motivates buyers today and tomorrow— can influence buyer motivation and also provide valuable experiences that customers will want to receive again and again.
To accomplish this, marketers must shift their mindset from one that prioritizes selling more products to one that prioritizes creating useful interactions for their customers. You can add more personalization to your communications with potential customers using clearoutphone factoring in location, preferred language, and time zone.
The goal should be to anticipate your customers’ needs, whether that means saving them time or making a difficult task easier.
Marketers must take a step back and ask themselves:
- What problem are we solving for our customers?
- What’s the consumer going to want to do next?
- And how can we make things easier for them?”
- Analyze & retain customers
If you’re a marketer, you understand how difficult it is to craft the perfect message for your target audience while also attracting and retaining them.
However, by leveraging data-driven marketing and intent data, you can gain real-time insights into what clients are looking for on specific problems and solutions.
These insights into existing customers enable you to upsell and anticipate problems rather than being caught off guard by clients who refused to renew or bought a product from a competitor you were unaware of.
4. Lead scoring and account prioritization
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Predictive purchase data can help you choose a lead scoring system. Priority should be given to companies that express interest and purchase intent prior to engaging in a competitive bidding procedure.
Exceed Your Sales Targets with Buyer Intent Data
Brands in all industries must be present where the consumers are— at all times and in all places. It’s safe to say that AI, data science, and other advanced technology are changing the way marketing works, and companies are naturally using it to boost their sales process.
But, just like any other type of data, intent data is not without flaws.
Although intent data can be extremely valuable on its own, it works best when combined with other data points such as firmographic/demographic, technographic, and engagement metrics to create a holistic scoring model that also takes into account qualifying criteria and engagement. When used correctly, Intent Data can be a powerful predictor of which accounts are most likely to purchase your product or service.
