Practices

B2B Data Accuracy: Understanding Job Changes

Imagine spending weeks crafting the perfect marketing campaign, only to find that 10% of your contact list is no longer valid. Understanding job changes and delays in updating professional profiles to maintain accurate B2B contact data.

Thomas Cornelius /June 18, 2024 / 4 min read /6 sections

Line-engraving of a row of engraved office-door nameplates, one plate being ground blank and re-etched with a fresh name while a cyan-to-violet band lights only the few plates still current: B2B contact records go stale as people quietly change jobs.

Cream line-engraving portrait of Daniel Conn, Co-Founder, graph8 and GTM Strategist. — Leader spotlight
About 4 percent of a contact list changes jobs every month, and half of those people wait months to update their profile. Refresh once a year and you are already selling to ghosts. We rebuild against open data, scraping, and purchased records every week, which is why the decay stops around 12 percent instead of compounding past 25.

Daniel Conn Co-Founder, graph8 and GTM Strategist

Imagine spending weeks crafting the perfect marketing campaign, only to find that 10% of your contact list is no longer valid. This is the reality for many marketing teams, as job changes and delays in updating professional profiles wreak havoc on data accuracy. In the fast-paced world of B2B marketing, maintaining accurate contact data isn't just a luxury:it's a necessity. By understanding the dynamics of job changes and the typical delays in updating LinkedIn profiles, marketing teams can set realistic expectations and develop strategies to keep their data clean and actionable.

Job Change Frequency and Update Delays

People change jobs approximately every 2.73 years, translating to an average monthly job change rate of about 4%. However, not everyone updates their LinkedIn profiles immediately after changing jobs. Some do so right away, while others might delay by up to three months or more. This variance means a significant portion of contact data can quickly become outdated, impacting the quality of B2B databases.

Consider a marketing manager named Jane who relies heavily on her contact database for outreach campaigns. Each month, about 4% of her contacts change jobs. Of these, half update their LinkedIn profiles within the first month, while the rest may take up to three months to do so. Jane's challenge is clear: without regular updates, her contact list's accuracy diminishes rapidly.

The monthly move

People change jobs roughly every 2.73 years, about 4 percent of a list each month. Half update their profile inside the first month, the rest take up to three, so the record on the plate lags the person behind the door.

Cumulative Effect on Data Quality

Let's break down the impact over three months. In the first month, 4% of contacts change jobs. Of these, 50% update their profiles immediately, leaving 2% without updates. In the second month, another 4% change jobs, with 50% updating right away. Additionally, 30% of the previous month's 2% (0.6%) update now, resulting in 3.4% without updates. By the third month, the cumulative effect is even more pronounced.

For Jane, this means that even with diligent efforts, the lag in updates leads to a growing portion of her contact data becoming stale. After three months, she has:

2% without updates from the first month,
3.4% from the second month,
4.38% from the third month.

Stale, month by month

The lag compounds. Un-updated records reach 2 percent after month one, 3.4 percent after month two, and 4.38 percent after month three, so quarterly refreshes let the decay pile up before anyone catches it.

Implications for Marketing Teams

For marketing teams, this cumulative effect underscores the need for frequent data refreshes. Relying on annual or even quarterly updates can lead to significant data decay. Instead, a proactive approach is essential:

Frequent Data Refreshes: Regular updates are crucial. Automated systems can help validate and update contact information more efficiently.
Multiple Data Sources: Combining open data, web scraping, and purchased data ensures a more complete and current contact list.
Understanding Industry Variances: Certain industries experience higher turnover rates, necessitating more frequent updates. Tailoring data management strategies to these variances can enhance accuracy.

Comparison of Observed vs. Calculated Data Quality Rates

At graph8, our data shows that approximately 12% of contacts are no longer at their company, slightly higher than the calculated 9.78%. This discrepancy can be attributed to several factors:

Employees Leaving Without Updating Profiles: Some individuals may never update their profiles.
Internal Role Changes: Employees who change roles within the same company may not update their LinkedIn profiles.
Higher Turnover Rates in Specific Industries: Certain industries naturally have higher turnover rates.

These factors highlight the importance of a strong data management strategy that accounts for these delays and inaccuracies.

Model vs the field

The math predicts 9.78 percent of records gone stale. graph8 measures about 12 percent in the field, a 2.22 point gap from people who never update, internal role changes, and higher-churn industries.

graph8's Approach to Data Accuracy

At graph8, we understand these challenges and have developed a complete approach to maintain data accuracy:

Using Open Data: We use open data from the web to supplement our databases.
Web Scraping: Our advanced techniques capture the latest updates and changes in professional profiles.
Purchasing Data: We buy high-quality data to ensure complete coverage.
Weekly Updates: Our commitment to weekly updates helps us maintain the most accurate contact information.

These methods allow us to provide the most up-to-date B2B data available, helping our clients maintain high-quality contact lists and execute effective marketing and sales campaigns.

Conclusion

The 12% rate of contacts no longer being at their companies aligns with the expected cumulative effect of job changes and LinkedIn update delays. For marketing teams, this highlights the importance of continually updating and validating B2B data to maintain high-quality contact lists. At graph8, our proactive approach ensures that we mitigate inevitable data decay and support our clients in achieving their marketing and sales goals. Understanding the dynamics of job changes and update delays can help marketing teams set realistic expectations and develop more effective data management strategies. By focusing on data accuracy and utilizing a variety of data sources and techniques, marketing teams can stay ahead of the curve and ensure their campaigns reach the right contacts at the right time.

graph8 light-abstract closing band: the architecture, running. — Re-etched weekly
The name on the plate is always going out of date. graph8 re-etches the whole list every week, so the record matches the person behind the door instead of drifting a quarter behind them.

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