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What Is the Reality of
Data Utilization in Market Development?
In the B2B market, leveraging AI to approach buying groups and multiple stakeholders is highly effective for achieving more accurate and impactful lead forecasting, personalization, predictive analysis of customer behavior, and sales efficiency. Because AI recognizes patterns and makes predictions based on vast amounts of data, higher data quality enables AI to generate more precise and personalized strategies. Utilizing AI with high-quality data is expected to significantly improve the overall efficiency and results of sales and marketing activities in the B2B market.
This article summarizes the importance of data quality in AI utilization in greater detail, divided into three key stages.
What Is Data Quality?
Data Quality refers to how well data is suited for its intended purpose. Generally, the following six elements constitute data quality.
- Accuracy
How accurately the data reflects the actual state of reality.
- Completeness
Whether all necessary data is present and no information is missing.
- Consistency
Whether data is maintained without contradictions across different systems or locations.
- Up-to-dateness
Whether the data is current and free of outdated information.
- Reliability
Whether the data is obtained from a trustworthy source.
- Availability
Whether the data can be utilized whenever it is needed.
With these elements in place, companies can make faster, data-driven decisions.
For a more detailed explanation of data quality, please also refer to this article.
What Is Improving Data Quality, Essential for B2B Data Utilization? | Blog | uSonar ▶
Data Quality and AI Utilization in Lead Qualification
Lead qualification is the process of identifying high-potential prospects from the pool of identified leads. By prioritizing contact with customers who show a stronger interest in your products or services, you can conduct sales activities more efficiently. Lead qualification has shifted from an era where sales teams relied on intuition and experience to identify key accounts, to an era where AI is utilized to allow more time for direct customer engagement. Assigning scores to leads based on their potential and prioritizing those with higher scores is one of the primary functions that AI provides in the B2B market.
Specifically, by integrating and maintaining the following data points internally, it becomes possible to more accurately identify prospects with high purchase intent.
- Past Lead Interaction History
- Website Access Information
- Search Content Trends on Comparison Sites
- Data Held in CRM/SFA
Data Quality and AI Utilization in the Marketing Process
Personalized marketing is a strategy that delivers optimal messages and content based on the specific needs and behaviors of customers. By identifying the characteristics of customers who are expected to generate higher profitability through data and AI, companies can clarify the needs and pain points of specific customer segments, providing high-precision insights into the information and solutions they seek. A key point in leveraging AI is establishing a workflow that enables the efficient execution of appropriate value propositions within account-specific journey maps (also known as Account-Based Experience or ABX), thereby bringing high productivity to marketing and sales teams. By promoting AI-driven personalization using high-quality data, companies can deliver the right information to the right accounts at the right time.
Specifically, it is possible to achieve higher-precision personalization by utilizing data with the following characteristics:
Data Quality and AI Utilization in Customer and Behavioral Analysis
With the advent of predictive analytics, it has become possible to dramatically improve the ability to predict the future purchasing potential of accounts, rather than just identifying targets on an account basis through lead scoring. To predict future outcomes based on behavioral patterns, accurate and high-precision data regarding customers is essential.
Particularly in the B2B market, since purchase decisions are made by multiple stakeholders (buying groups), it is important to manage customer data in units of "companies" or "buying groups" rather than "individuals." It is crucial to understand the entire purchasing process by optimizing the insights provided by AI based on the behavior and relationships of the entire group, rather than on an individual basis.
For example, multiple individuals with different roles, such as marketing managers, technical staff, and financial officers within a company, are involved in the purchasing process. By integrating and managing data for all these members, AI can provide personalized messaging and content tailored to each of their interests and needs. This promotes an improved customer experience and facilitates the closing of transactions.
Conclusion
In the B2B market, the greatest challenge in effectively leveraging data across an entire organization lies in the fact that data exists in fragments across multiple tools and vendors. Because the sources for account and contact information, corporate attributes and intent, and deployed technologies and competitive engagement status are all different, information regarding a single account has been scattered, creating numerous barriers to integrating all this data and keeping it up to date.
Our customer data integration solution, uSonar, is equipped with LBC, one of the largest corporate information databases in Japan. Many companies use the customer information platform integration and data cleansing functions powered by the high-quality data provided by LBC to realize more efficient sales and marketing activities.
By matching your internal data with LBC data, you can identify and correct duplicate or inaccurate information, enabling you to maintain the latest data for your target accounts.
Furthermore, we provide features such as predictive analytics and AI-driven list generation based on the integrated customer information platform.
For more details, please feel free to contact us via this page.
