Continuous Data Enrichment – a Revolution in Data Quality Process

When B2B Marketers and Sales Ops leaders are facing the data quality problem, they’re inevitably draw their attention to the data enrichment and data cleansing tools – the backbone of their future B2B data quality process.

Data enrichment and data cleansing tools – the backbone of a B2B data quality process

All data enrichment and data cleansing tools, however, have not been created equal. The majority of the “classical” vendors you’ll meet in that space, such as Clearbit, FullContact, Uplead, DiscoverOrg and others are generally very capable solutions, yet they can only be utilized for what we at MARCOM Robot call a “legacy data enrichment scenario”. The scenario is very simple:

1. Marketing team’s generating leads that need to be enriched
2. Classical data enrichment engine attempts enriching the leads generated by marketing
3. Some leads have been successfully enriched (40-60%)and some haven’t (40-60%)

So, nothing wrong with that, right? Well, yes… if you’re aiming at the enrichment rate of 40-60%, then look no further. In fact, for some organizations this is a good enough and we totally understand that. If your motto is“don’t settle”, then you may want to take a closer look at continuous data enrichment tools, such as MARCOM Robot Data Quality Engine. And here’s what it is in a nutshell:

1. Marketing team’s generating leads that need to be enriched
2. Continuous data enrichment engine attempts enriching the leads generated by marketing
3. As the result, some leads have been successfully enriched (40-60%) and some haven’t (40-60%)
4. Continuous data enrichment engine moves all records that haven’t been enriched from the first attempt to a special queue for re-processing and re-crawling
5. As the result, continuous data enrichment engine returns the missing data for the records that haven’t been enriched within 48 hours. The enrichment rate with that approach is north of 90% which is unheard of in the industry.

Continuous data enrichment ensures a more reliable and accurate data quality process

Of course, like with any data enrichment and cleansing case a lot depends on the quality of the input data. Continuous data enrichment, even though being far superior than legacy enrichment process, can’t help if the input data that you’re feeding it is not accurate on the first place.We would recommend all organizations that are taking data quality seriously, implement an email verification process on their registrations forms and subsequent email quality scoring to ensure that the enrichment-ready data is as accurate as it can be to ensure the success rates upwards of 90%.