![]() ![]() The reason of course was that they were mailing to a wide target, including many folks with bad data. Most likely, you are marketing to people that have no need for your service and this process is bringing down your overall results.įor example, we recently worked with a client whose click-through rates hovered around 0.5%–much lower than 1-4% we see for general mailings. Bad Data Kills Marketing Resultsĭo you have low click-through rates or engagement activity? Does Management always ask why Marketing’s results are lower than industry standards? #CRMFUSION SINGLE TABLE DEDUPLICATOR SOFTWARE#If 20-30% of your data is bad, that’s needlessly hiking up the cost of multiple software subscriptions. As your organization matures, you’ll have data living across CRMs, marketing automation solutions, ABM platforms, and others. Most SAAS platforms charge based on record count. “You are over your data limit.” How many times have you received this message from Marketo or other software services? Source: RingLead Bad Data Hikes Up Software Costs This great infographic from RingLead breaks down all the costs. Even if you think that $100 per record is high and take a conservative approach at $10, that’s still $200K. If you have 100,000 records in your database and 20% are inaccurate (and that’s a conservative estimate), that’s $2M down the drain. Sirius Decisions estimates that between the tangible and perceived costs, organizations spend an average of $100 to maintain every record in their database – even the dirty ones. Why Bad Data Hurts Your Business Bad Data Costs Moneyĭid you know that a bad record can cost as much as $100 to maintain? #CRMFUSION SINGLE TABLE DEDUPLICATOR HOW TO#Part 2 dives deep into how to execute in Marketo. Part 1 covers all the strategy and process. Learn how to reduce your database size by 10-40% to remove junk, reduce software licensing costs, and improve marketing results. Step 6 – Delete the Inactive (but only after a Wake The Dead campaign!).Step 3 – Purge Recently Deleted Salesforce Records. ![]()
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