//How to Fix B2B Data Fusion
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How to Fix B2B Data Fusion



B2B marketers are in trouble when it comes to data. Understanding the data is essential to improve marketing and business performance. According to Dun & Bradstreet (D & B), published recently the sixth annual report on B2B marketing data

lost confidence in the data.

Only 50% of those surveyed as part of the D & B survey expressed confidence in the quality of their data, up from 75% in 2017. And only 11% expressed extreme confidence in 2018. "The lack of trust of B2B organizations in their data hampers the ability to deploy key business and marketing initiatives," concludes the D & B report. "Instead of creating opportunities, it creates chaos."

A typical example: Only 38% of marketers surveyed said that account marketing (ABM), a leading data-driven marketing tactic, was currently part of their marketing strategy. The report notes that the ABM needs quality data to identify and target key accounts and targets, reach them through different channels and provide relevant content. Marketers are forced to rely on outdated, conflicting, misleading or otherwise distorted information, which is costly to them. They have a limited or inaccurate view of customers or prospects.

Meanwhile, data quality is the key to providing personalized content, essential to improve the customer experience and generate revenue. VisionCritical predicts that the customer experience will surpass the price and product as a brand differentiator by 2020, and Forrester estimates that an increase only 10% of data accessibility will result in more than an additional $ 65 million. net income for a typical Fortune 1000 company.

What should a marketing specialist do? In my company's work with data, we've discovered eight steps to make sure your data works for you, not against you.

The 8 Steps to Turbocharging Your Data

1. Commit to improving the quality of data.

It is important to improve the quality of data to ensure that your company's data is accurate, up-to-date, complete, and consistent, and that it provides the depth of insight required for a given business. solid decision making. Define the quality of the data according to the objectives of the company.

2. Assign the property of data quality.

Give a person primary responsibility for the quality of the data. This is your new data manager. This person should work with a team, including members with roles such as software developer program manager, project manager, data manager, and data analyst.

3. Refine your data collection process.

Do not drown in excessive information. Determine exactly what types of data are relevant to answer your questions and help you make informed decisions that meet your business goals. Make sure your data comes from reliable and knowledgeable sources.

4. Check the contact data as they are collected.

Validate the information systematically or manually before entering it into a database. Pay attention to email addresses and missing information. Engage your customers directly via a phone call, web form or online chat. Once you have the updates, make sure your database is complete.

5. Standardize your data.

As the information is collected from various sources, your database may include various spellings or formats of the same data point. For example, although you know that the United States, the United States, and the United States are the same, marketing automation platforms and CRMs consider them different, which can alter your lists. smart, your scoring and your segmentation. Create standardization, or standardization, of smart campaigns in Marketo, or use a third-party tool, such as RingLead Data Management Solutions.

6. Identify and purge duplicate records.

Multiple duplicate fields of information can hinder the automation of marketing. Configure trigger alerts for automatic notifications. Check your database for suspicious entries to manually examine.

7. Integrate marketing and sales data.

Despite years of effort to align these functions, it is still common for marketing and sales to use different customer relationship management and automation systems to manage data, creating confusion and confusion. errors. The organization of all data in one location is the perfect medium for personalized marketing that delivers the right content at the right time.

8. Conduct regular reviews of the data.

Develop and implement a strategy for regular database reviews. Increase real-time verification with regular block processing to ensure the integrity of contact data.

These eight steps will help you better understand your data and measure and improve quality over the long term. Is it a lot of work? Yes, the best-in-class data collection and management tailored to the needs of your business require serious and continuous effort. But the stakes are high and the direction is clear.

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