Capital Markets and Real Estate Data Intelligence, Powered By Salesforce

Our Core Operating Principle: Salesforce should improve your firm’s data intelligence, not complicate it.

Our capital markets practice routinely receives calls from our partners and clients asking us for Salesforce Preqin integration, or Pitchbook, CapIQ, Equilar, and other data providers. What’s more important is how their peers in the industry are leveraging Salesforce as an output device, rather than another silo’d input device. The challenge here is whether your firm is a private equity firm, direct lender, hedge fund, VC, REIT, or investment bank; you have a lot of data from many disparate sources. 

To name a few: if your information stack includes Preqin, Pitchbook, CapIQ, Equilar, Bloomberg, Crunchbase, Reonomy, Compstak, Yahoo Finance, PrivCo, and others, this article is for you. 

If any (or, for larger diversified institutions, all) of these names are incorporated into your information stack, it’s probably reasonable to assume that you’re having internal debate or hardship about surfacing all of this data into a useful format that can be put to work by your deal teams and IR. Even more challenging, is when your primary method of consumption for all of this information is through the websites of these providers directly, which is separate from your pipeline tracker and IRM (Investor Relations Management) platform. This is the core problem that we set out to solve for our capital markets clients.


How We Do It:

1. Consolidate IR, deal team, and operations on one central platform

Before we get excited about consolidating data sets into a more useful format, it’s important to get everyone on the firm using the same platform first. We choose Salesforce as the platform of recommendation for capital markets firms for many reasons that I elaborate on  in this article! To sum it up though, Salesforce provides an excellent platform for fundraising, deal team pipeline (and sub-pipelines for different strategies like direct lending/credit, buyout, growth equity, etc…), and even tracking capital structures, quantum, and deal metrics for future bench-marking. Having all of this data in one place is critical for normalizing the inflow of external data.

2. Categorize like-datasets by Salesforce objects

Imagine an Excel workbook where each tab represents a different type of data that your firm maintains. Tab 1 could be limited partners, and each column would represent a datapoint like Total Dry Powder (MM) or Investment Preferences/Restrictions. Tab 2 could be target/portfolio companies, and each column would be created for operating metrics, financials, key contacts, introduction source, and dozens more fields. Subsequent tabs in this “workbook” would be funds, deals, intermediaries,  and so on. Now that we have all of our data categorized, let’s take all of our data providers on one side, and match them to the accompanying “tabs” that they provide data on. It will likely look something like this:

If you’ve made it this far, you’re ready to plan your data integration strategy!

3. Ensure your data providers have provisioned API access

There are paid subscription options offered by most of these data providers to digitally expose access to their APIs so that we can leverage to connect directly for a one-way synchronization of data from the source data providers to the target Salesforce database. Before we begin to execute the data strategy, you’ll want to ensure that you have the necessary license type with each provider to access the APIs.

4. Select the right data sets

All of these data sets have dozens (and in some cases, hundreds) of fields per record. Surely we do not want to capture all of this data in Salesforce. For this reason, it’s important to set boundaries for the types of records and fields that we want to pipe into Salesforce from any 3rd party source. This is an exercise that must be run for each data source separately in order to inform the next component of your strategy.

5. Map the right data to corresponding records

If we’re piping more than one data source into Salesforce, it will be critical for us to map the correct API  endpoints and fields from the source to the Salesforce object fields. This will be divided by type of the record, for example, an LP record will have synchronization with Preqin data sets, while a portfolio/target company record will have synchronization with Cap IQ data sets.

6. Use pre-built middleware to populate CRM with source data

Now that we have the data sources divided by category (tabs in the Excel Workbook exercise) and the permissions necessary to integrate the data sources themselves, we’re ready to connect them to Salesforce leveraging pre-built middleware. Here, we’re using EasyAPI which connects to each of the most common capital markets data providers on one end, and Salesforce endpoints on the other. Check out the examples of the finished products below:

First Use Case: Preqin data populating LP institution and contact details in Salesforce:

Second Use Case: Preqin populating portfolio company and fund raise data in Salesforce:

Third Use Case: Reonomy populating property, ownership and mortgage data in Salesforce:

Tying it all together: Better data informs better process

Part of our job as a management consultancy is to view the bigger picture. Our clients may bring us a tactical problem such as deal teams lacking visibility into pipeline and easily accessing information from anywhere, or IR requiring a reporting mechanism and portal for LPs. We take this as an opportunity to try to dig deeper into the primary issue, which almost always has to do with data being inaccessible, or otherwise underutilized. If we can help our clients aggregate, transform, and leverage their data, we can improve most of their internal processes. To find out how this might work at your firm, get in touch with us today

Written by
Gregory DelGenio

Gregory DelGenio

Partner and Chief Revenue Officer

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