24 March 2021
AI and automation will be a staple of the B2B sales processs according to Forrester. Sales Enablement is booming in the US,…
7 December 2017
When sales intelligence solutions were first launched twenty year ago, they operated as stand-alone web browser services. While Customer Relationship Management platforms (CRMs) existed back then, they were behind-the-firewall installations such as Siebel, and the cloud really didn’t exist. Integrations between CRMs and sales intelligence solutions were rarely seen and were rudimentary due to complexity and security concerns. In 1999, Marc Benioff left Oracle and founded Salesforce.com as a “no software” CRM hosted in the cloud. Sales and CRMs changed quickly with the launch of SFDC, but sales intelligence operated as a distinct service for nearly another decade.
Salesforce made it much easier for vendors to integrate with their platform when they launched the AppExchange in January 2006. This was the real point at which various cloud services could partner with Salesforce and create joint value. As Salesforce is now the leading CRM, sales intelligence vendors generally build their first CRM connectors for the AppExchange. In the Sales Intelligence category alone, there are 154 AppExchange solutions available. It would be easy to get lost amongst all the vendors.
In 2017, however, any evaluation of a sales intelligence service should include a review of the CRM connector. Don’t treat CRM connectors as a simple checklist item. They are critical to the ROI you will enjoy from your Sales Intelligence vendor. As sales reps now live within CRMs, a proper evaluation of sales intelligence vendors must include an evaluation of the Sales Intelligence vendor’s CRM connector. This evaluation should include content, functionality, and workflow.
While vendors initially offered simple functionality focused on Send to CRM for accounts and leads, sales intelligence vendors such as Sparklane now provide deeper integrations for the major platforms. At this point, few sales intelligence firms offer such limited functionality within Salesforce and Microsoft Dynamics. However, you may still find Send to CRM as the full feature set of connectors for less popular CRMs.
The next level of integration involves the display of sales intelligence within CRMs. This is usually done as a set of I-frame views (those expand/collapse sections seen in account and other record types). Some vendors choose to create separate tabs for their service instead of supporting I-frames, but this strategy is sub-optimal because sales intelligence is not displayed in the context of specific records. Sales reps are unlikely to go to a separate tab to lookup account, contract, or lead information. Furthermore, I-frames allow the sales rep to view additional content beyond basic firmographics and biographics including sales triggers, family tree linkage, and company contacts.
A second reason to display records within i-frames is support for “stare and compare” functionality. If a record has not been recently updated or the record has limited information, the user can quickly update the record. A “stare and compare” update displays the record as it exists in your CRM against what is stored in your sales intelligence vendor’s data warehouse. Sales and support reps can then choose to fully or selectively update the record with the latest third-party intelligence. In most cases, a full update is performed, but there may be data the sales rep does not wish to override such as direct dial phones. In this case, the rep would only update a subset of the fields. Stare and Compare functionality improves data quality, raises sales rep confidence concerning CRM data quality, and reduces the time spent entering CRM data.
Another handy feature is auto-matching which populates CRM records based upon a few key fields (e.g. company name, city, region). Like stare and compare, the goal is to reduce time spent keying in data while improving data quality. Auto-match has the additional benefit in that it populates CRM fields the sales rep is unlikely to know such as turnover, industry code, and registration number. What’s more, key fields are standardised helping ensure proper segmentation and reporting.
A proper review of sales intelligence connectors includes an evaluation of contacts. Not only should the system display contacts, but they should be easy to filter by job function so as to quickly identify the best prospects at an account. The sales rep can then select the best fit candidates and quickly add them as contact records. As many B2B sales and marketing departments have adopted Account Based Marketing (ABM), the ability to quickly identify strong prospects at target accounts is critical to establishing a beachhead or expanding to additional departments at an account.
Similar to the ability to filter contacts, sales intelligence vendors should also support sales trigger filtering within the CRM. Category filtering and keyword searching allow sales reps to identify the most valuable trigger categories for their company. Easy trigger filtering assists with account planning and messaging. Sales triggers also provide quick hooks for gaining the attention of prospects and help raise the confidence of sales reps. Of course, sales triggers also provide a reason to check in with a customer or prospect and may even result in a modification of close likelihood.
If you are evaluating sales intelligence connectors for Salesforce, ask whether triggers are shared with the Salesforce Chatter social messaging platform. Automated Chatter feeds assist with account management by automatically delivering sales triggers concerning followed accounts. Thus, account teams can monitor key accounts via Chatter, providing a much timelier and structured account monitoring workflow.
When evaluating CRM connectors for sales intelligence, don’t treat the presence of a connector as a pro forma checkbox item. There is a great deal of variability in functionality between vendors and across CRMs. A well-designed CRM connector is critical to obtaining a strong ROI on your sales intelligence expenditure.