Buyer Intent Data
Article | March 6, 2023
Intent data is an essential piece of the account-based marketing puzzle. It’s the type of data that can give B2B companies a competitive edge as they look to identify engaged, active prospects at prioritized accounts that show a clear pattern of interest in a product, service, or solution. As importantly, intent data can pinpoint signals in a buyer’s journey that lets you know what their next step might be, helping you target them with personalized, contextual messaging.
There are a couple of flavors of intent data, but in this case, third-party intent data is the focus.
Third-party intent data originates from external sources and may include many potential online interactions that have occurred away from your website and your company’s interactions. Website visits at competitor sites, webinar attendance, downloads, product reviews, social media interactions, and online subscriptions to publications in your industry or sector are fair game for third-party intent data insights. Like an intricate spider web woven from numerous data points, third-party intent data offers a view of online behavior for potential prospects as they traverse their buying journey.
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Buyer Intent Data
Article | October 7, 2022
Introduction
The application of AI marketing technology is picking up pace because of its many advantages. According to a 2020 Deloitte survey, 74% of AI adopters agree that AI will be a part of all their enterprise applications by 2023.
What does an AI-based marketing strategy look like, and how do you make the most of it? This article gets into the nitty-gritty of AI marketing technology and how to implement it in ABM so you can maximize your business performance and outputs.
AI’s Role in Marketing
Thanks to its accuracy, B2C businesses use AI marketing technology to target their customers with product or service recommendations. The following are some use cases of AI-based B2C marketing:
Personalization
AI helps businesses with their 1-to-1 marketing strategies by personalizing their content to cater to every segment.
Event Communication
Emails informing customers of upcoming sales, special access, or exciting offers are sent out via AI technology. Weekend offer emailers, special discount codes, and new product updates are a result of event communication automation so that customers can be informed before time about upcoming events.
Real-time Content
Trending topics, investments, event promotions, webinars, customer feedback, product availability, bestselling combo, weather reports, and new blog post updates are provided in real-time to maintain an active connection with customers.
Businesses do this by using the ‘open time content’ AI technology. Manually executing 1-to-1 marketing strategies is nearly impossible, impractical, and does not see much success. AI helps streamline these strategies and executes them effortlessly.
What Goes into Creating an Effective ABM Strategy?
For an ABM strategy to work, businesses need to follow these steps:
Preparing for the ABM Strategy
Organizational readiness is crucial for implementing ABM. Make sure you have a budget and an achievable timeline to execute the strategy, team members who can anchor it, and an understanding of ABM metrics so you can make the most of it.
Synergy Between Marketing and Sales Teams
Your sales and marketing teams should be in sync and not at loggerheads due to account-level communication issues. Discussing the benefits of ABM with both the teams beforehand and coming to a strategic agreement to implement ABM can help them align their goals while executing the ABM strategy.
Identifying Target Segments
Your ABM strategy can do wonders for your business only if you have a precise segmentation of data. Use dimensions like business size, annual revenue, current spending, projected spending, targeted products, geography, open opportunities, closed opportunities, etc., to identify your target segments.
Zeroing-in on a Priority
Having a clear priority helps you streamline your ABM strategy. It should either be acquisition (acquiring new accounts), retention (retaining existing accounts), or expansion (expanding the scope of accounts). Without a clear priority, any ABM strategy may not yield expected results because the efforts won’t be concentrated towards a single goal.
Leveraging AI in ABM Strategy
In an interview with Media 7, Daniel Englebretson, founder of Khronos, spoke about AI’s impact on the future of ABM.
“From my perspective, B2B marketers have faced countless challenges that have formed the basis of new technology – problem brings a solution. I expect AI will solve identity resolution, resolve data challenges, and enhance targeting. I expect AI will address 1:1 content at scale, unlocking the rapid deployment of 1:1 brand experiences.”
Introducing AI into your ABM strategy can help you in the following way:
Content Personalization
Once you know your customer’s pain points and interests, you can focus on providing them personalized solutions, products, or services they desire. Of course, personalizing content is complex, but AI makes it easier by offering the technological capacity to deliver what your customer wants.
Efficient Resource Management
Without customer profiling, an ABM strategy cannot achieve the expected output. AI can assist with data crawling the internet to find out important customer information. Also, it segments data acquired from CRM, which gives you more information about a customer than any other generic data. This data is helpful for lead qualification and creating heavily personalized content for a customer.
Since AI does all the heavy lifting, you can allocate your resources to building and nurturing a relationship with the customer.
Automation
AI-based marketing in ABM generates automated insights for lead generation. It also highlights campaign performance related to specific, high-value accounts and suggests steps to engage a prospect.
Digital marketing and automation are a dynamic duo where AI brings about intelligent marketing automation. Efficient email campaigns are run when executed by automation. Email marketing companies like MailChimp target customers based on insights to achieve more conversions. When AI and big data use CRM data, large chunks of user information can be collected from different platforms. This information can help with formulating a successful ABM strategy.
ABM Optimization and Predictive Insights
To analyze intent, AI processes data in real-time and gives predictive insights to help with ABM optimization. As a result, it is easier to merge data from different sources with AI-enabled tools, achieve predictive analysis, manage recommendations in real-time, and understand competitor strategies through social media. AI can also interpret images correctly.
Enhancing Communications
Use AI for building a strong relationship with your customer. Personalizing communication by using customer data can be easily achieved with AI.
What Is the Future of AI-enabled ABM Strategy?
ABM, with an AI marketing strategy, has a bright future ahead of it. Demandbase recently conducted a survey in which they found that 80% of marketers had plans to integrate AI into their ABM marketing strategy. Another survey conducted by MarketingProfs concluded that businesses that used AI in their ABM strategies had 59% higher closing rates as compared to others. They saw a 58% increase in their revenue and a 52% increase in their conversions.
Ways Salesforce's AI Einstein Aided U.S. Bank in Growing Revenue
The U.S. bank used Salesforce’s sales cloud AI, Einstein, to boost their revenue. Their lead conversion rate increased 2.35 times after implementing Einstein. They were able to create a model to predict lead conversion. They did this by using Einstein to search through customized historical lead data.
“We work to build high-quality, personalized relationships between our customers and their financial advisors or commercial bankers. There is nothing that replaces that person-to-person interaction. What AI allows us to do is augment that relationship. We can provide our teams with better data and smarter insights, which helps them establish stronger relationships.”
– Srini Nallasivan, Chief Analytics Officer, U.S. Bank
Summing It Up
AI-based marketing can enhance your ABM strategy only if qualitative data is available. Therefore, businesses will need to have clear marketing goals and turn data into an asset.
FAQs
What are the challenges in the AI-based ABM strategy?
Managing, protecting, and enriching data obtained from CRM and other customer support systems can be challenging.
How can AI help in strengthening your ABM strategy?
AI helps with personalizing content, automation, ABM optimization, and providing predictive insights for lead conversion.
What does a strong AI-based ABM strategy do for your business?
A strong AI-based ABM strategy helps with account profiling, analytics, reporting and hyper-individualized content, which leads to increased lead conversion.
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Programmatic ABM
Article | June 9, 2022
Third-party cookie restrictions or outright bans were an inevitable step in the evolution of data protection. As a result, B2B marketers are preparing for a cookie-less future in which third-party data will no longer direct them to potential clients. They must now prepare new tactics to execute account-based marketing (ABM) strategies.
Abhi Yadav, the founder of Zylotech, states that ABM strategies greatly depend on trustworthy data: “We believe the foundation for any successful ABM program lies in the ability to “trust” your data. This requires scalable, repeatable processes for data management and governance across all people, accounts, and activities.”
Abhi Yadav, the founder of Zylotech, states that ABM strategies greatly depend on trustworthy data: “We believe the foundation for any successful ABM program lies in the ability to “trust” your data. This requires scalable, repeatable processes for data management and governance across all people, accounts, and activities.”
In light of the demise of third-party cookies, where can B2B marketers turn for reliable information? Let us find out.
First-Party Cookies
When it comes to potential customers, first-party cookies are the most dependable source of information. These cookies assist in monitoring audience behavior when they visit our websites and engage with our content. Based on recent interactions, first-party cookie data will produce more relevant content.
Data Points
When developing ABM strategies, delve deeper into first-party data and use locations and keywords. B2B marketers can then contextualize the content and figure out what prompted the viewer to interact with it in the first place.
Tracking Technologies
Tracking technologies like reverse IP tracking are legal and can aid your ABM campaigns. This technology enables businesses to conduct reverse IP searches and access the top-level domain data that IP produces. The name of the business hosting that IP and the other details of those who registered the business IP can be accessed. Using this information, B2B marketers can develop an effective target list and pursue the target accounts with personalized content.
Contextual Advertising
Contextual advertising displays advertisements to website visitors based on the content they are currently viewing. As a result, the visitors find these ads relevant to their needs and are more receptive to them.
ABM Success Requires Reliable Data
Using primary data sources will provide direct feedback on the relevance of your content based on interactions with potential clients. As we enter this first-party world, you must remain agile, with new ABM tactics ready to guide clients toward successful partnerships.
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Buyer Intent Data
Article | September 11, 2023
Gain insights into 2023 buyer intent data trends. Explore key marketing technologies and strategies essential for businesses to enhance their ability to engage potential customers effectively.
Buyer intent data is indispensable for businesses in an increasingly fast-paced and data-centric account-based marketing (ABM) space. It serves as a compass guiding marketing and sales efforts by providing profound insights into consumer behavior and purchase intent. With this information, businesses can precisely target their targeted audiences, personalize their messages, and optimize their resource allocation, all of which result in higher conversion rates and a greater return on investment.
With rapidly changing customer behavior and evolving marketing space, buyer intent data has become the cornerstone of contemporary marketing and sales strategies. In 2023, it is set to reach new milestones, fueled by growing technological advancements and a deeper understanding of consumer behavior.
As a result, it is essential for B2B businesses and marketing teams to be aware of the emerging buyer intent data trends to adopt cutting-edge technologies and strategies that enhance their ability to understand and engage potential customers effectively.
Futuristic Buyer Intent Data Trends for 2023 and Beyond
In an era where competition is fierce and customer expectations are continually growing, harnessing the power of buyer intent data is not just advantageous; it's fundamental for achieving sustainable growth and increasing market share in the space. Furthermore, it bolsters customer engagement and loyalty by demonstrating a commitment to understanding and meeting their needs.
Businesses that embrace B2B buyer intent data gain a decisive advantage, positioning themselves as agile and customer-focused enterprises ready to thrive in the marketing domain. Consequently, staying informed about buyer intent data trends is not only a strategic advantage, it's a necessity for sustained growth and relevance.
Here are some of the latest buyer intent data trends that businesses must be aware of in 2023
AI-Powered Predictive Analytics
One of the most exciting trends in buyer intent data is the increasing role of artificial intelligence (AI) and predictive analytics. AI-powered buyer intent data tools analyze vast amounts of data to identify patterns and trends that might not be apparent to human analysts. This, coupled with predictive analysis, enables businesses to predict buyer intent more accurately.
With advanced AI algorithms, businesses are able to sift through vast datasets, recognize intricate patterns, and predict buying intent with unprecedented precision. This technological advancement enables companies to not only identify prospective customers but also create customized marketing strategies and engage them at the precise moment when they are most likely to make a purchase. In essence, AI-powered predictive analytics is elevating buyer intent data to an entirely new level, making it an invaluable asset for any forward-thinking business striving for marketing and sales excellence.
Integration of Multiple Data Sources
Buyer intent data relied on a single source of information, such as website analytics or email engagement metrics in the past. However, with increasing emphasis on understanding customer behavior, there's a growing recognition of a holistic view of buyer intent. This, in turn, is increasingly creating a need to integrate multiple data sources.
The trend of integrating multiple data sources provides a more detailed and deeper understanding of consumer behavior, thereby significantly enhancing the value of buyer intent data. Businesses can construct an extensive mosaic of each lead's digital journey by combining data from various touchpoints and channels, such as website interactions, social media engagement, email responses, and chat interactions. This multidimensional perspective provides more in-depth and accurate insights into buyer intent, allowing companies to tailor their marketing and sales strategies with unmatched precision.
Real-time Intent Monitoring
As businesses and marketers increasingly adopt advanced technologies, the days of post-event analysis are rapidly diminishing. Now, real-time monitoring of intent has become the primary focus. The strategy involves the use of innovative tracking technologies to detect and respond to buyer signals in real-time. The trend is increasingly gaining prominence as it allows businesses to respond to buyer signals as they happen.
When a potential customer exhibits strong purchasing signals, such as extended engagement with pricing pages, repeated product demo views, or initiating a live chat, real-time alerts trigger immediate action. This instantaneous response capability enables marketing and sales teams to provide highly relevant information and immediately deploy targeted messaging or offers, significantly increasing the chances of conversion.
Cross-channel Engagement
As businesses recognize the significance of engaging with leads and consumers across multiple channels, the need for innovative strategies, such as cross-channel engagement, is rapidly growing to ensure that businesses are present where their audience is, be it via email, social media, website interactions, or even chatbots.
In an era where consumers frequently switch between channels during the purchasing journey, cross-channel engagement ensures that businesses are consistently present and responsive. It improves the customer journey, enables complete data capture and analysis, and contributes to a more in-depth and accurate understanding of buyer intent. Cross-channel engagement enriches buyer intent data by providing businesses with a more detailed and real-time view of their audience's behavior and preferences, ultimately resulting in more effective marketing and sales strategies and stronger customer relationships.
Hyper-personalization
The hyper-personalization trend is ushering in a new era of consumer intent data utilization by bringing personalization to new heights. The approach utilizes the abundance of available consumer intent data and AI-driven content recommendation engines to deliver personalized experiences to individual leads and customers.
By analyzing a prospect's past actions, preferences, and interactions, businesses can create hyper-personalized content and offers that precisely align with their interests. It also optimizes time, ensuring that engagements occur exactly when a prospect has the highest possibility of converting. This level of personalization increases the chances of conversion as well as fosters a deeper connection between brands and their target audience. Hyper-personalization is not merely favoring consumer intent data; it is elevating it, enabling businesses to deliver exceptional, one-to-one experiences that boost engagement, trust, and brand loyalty.
The Bottom Line
Buyer intent data is the lifeblood of modern businesses, providing vital insights into consumer preferences and behavior. It enables companies to determine when potential consumers are prepared to buy, allowing timely and targeted marketing and sales efforts.
Staying informed about the latest buyer intent data trends enables businesses to employ cutting-edge technologies and strategies that improve their capacity to comprehend and engage potential customers. Companies can improve their techniques, enhance customer targeting, and optimize resource allocation by foreseeing and adapting to these trends. Furthermore, being aware of these trends is crucial for maintaining customer trust and compliance with evolving data privacy regulations, thereby ensuring the ethical and responsible use of data.
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