Data is the lifeblood of the modern business. But all data must come from somewhere. A lot of the key data that companies use today comes from sales reps, being the key customer-facing resources for the business. Only the sales field has insight into things like customer sentiment off the last video call or the nuances of how a customer communicates about capturing budget or competitive analysis.

Most organizations also have mandatory fields the rep must enter in Salesforce to capture information about why customers are interested in buying, the persona of the buyer at the customer, what problems they are trying to solve with the product, whether there is later upsell opportunity already discussed, who holds the budget, and more.

Because there are so many inputs that sales reps have to provide, it's good for everyone involved to automate as much data capture as possible. Using enrichment tools means that your sales rep no longer has to enter basic information like company addresses, phone numbers, or number of employees because this information can be automatically ported in from an enrichment platform. This leaves more time for the sales rep to focus on selling rather than data entry.

How data enrichment works

Fundamentally, every data enrichment tool works the same. I would break the enrichment process down into 3 main steps:

  1. Mapping
  2. Matching
  3. Updating

Mapping data

As an administrator setting up an enrichment tool, you are responsible for mapping the data attributes from the enrichment database onto your own database. Some of these are simple and straightforward (e.g. the vendor's "phone number" attribute matches to your account object's "Phone" field), while others require custom fields to map onto.

The first step in this process is defining what data do you need in Salesforce out of the dataset available from the vendor. Once this is identified, you will need to map those datapoints onto your existing Salesforce fields, or net new fields to be created.

⚠️
A word of caution: be careful when mapping data from enrichment tools into Salesforce, since you don't want the tool to accidentally overwrite important data.

Every enrichment platform nowadays has options on each attribute to either overwrite whatever data may already be in the mapped field, or to only "fill if blank" which will only store the enrichment data on a specific field if that field would otherwise be null.

Best practice for data enrichment is to map as many datapoints as you can to new custom fields specific to the enrichment tool. For example, you might have an entire set of fields being enriched by D&B and another entire set of fields being enriched by Zoominfo. If neither of these tools map onto the standard Salesforce fields, then you have the ability to pick and choose what data from your enrichment tools do you want to map over to the standard fields, either by a manual data cleanup exercise or through an automated process.

Matching records

Once you have setup your tool and configured the data mappings, congratulations, you can turn it on! While the tool is performing an enrichment job, it will go through a complex process of cross-referencing a record from Salesforce against their dataset and trying to return a match. The tool will generally compare things like account name or contact name, billing address, phone number, website or email address, and other firmographic and personal information to identify a match.

Each tool has their own proprietary matching algorithm, but they all basically work the same way insofar as they find matching records in their dataset to your Salesforce record, estimate the probability that each one is a "true" match, and pick the best of those options. Some tools can even map a confidence score back into Salesforce so you can see how reliable the enrichment data might be.

Updating records

Once an enrichment job has found a match, the final stage in the process is to actually push the updated enrichment data into your system. Most enrichment tools have up to the following three modes:

  • "Create a record" mode: with this mode, you can create a new record in Salesforce entirely from the enrichment dataset. This could be a Lead, a Contact, or an Account. This can save your sales reps a ton of time that they otherwise would have spent doing data entry.
  • "Instantly enrich" mode: with this mode, you can create your own new records in Salesforce, but once they are created, the system will immediately cross-reference the enrichment data set. If a match is found, the fields you mapped will be automatically updated by the tool.
  • "Rolling enrich" mode: with this mode, the tool will go through every record in your Salesforce instance on a regular basis in batches. Every 2-3 weeks, you can expect that every record in your system will have been re-checked for a match and re-enriched in case of any data having been changed in the enrichment dataset since the last enrichment job.

Each of the above will follow the field mappings you set up, so whatever attributes you have aligned to the fields in your Salesforce instance will be pushed over to those fields on the record which was matched against.

Conclusion

Data enrichment tools are a necessary part of the modern CRM tech stack. Letting computer automation handle the heavy lifting of mapping business data into your Salesforce means your sales reps get to focus on what they do best – closing deals. Enrichment data also enables your analytics teams to understand more about your customer base who's buying and who's not buying, and better inform product and sales strategies moving forward.

Know that they are not always perfect. Business are changing every single day, and no enrichment dataset can ever be 100% accurate. But even with that in mind, using an enrichment tool is a game changer for increasing the accuracy and completeness of your org's data, and increasing the efficiency of your sellers.

Tagged in:

Data Salesforce