If Data Hygiene is Affecting the Bottom Line, Start Investing in Your CRM

The CRM is at the heart of (in fact, IS the heart of) most revenue organizations today, and rightly so. It’s probably one of the first serious tech investments a business makes, because of the direct impact it has on sales productivity and revenue generation capacity of these businesses.

Salesforce has been the trailblazer for CRM adoption across businesses of all sizes and types. By evolving as a system of record as well as as a system of engagement (with the help of its ecosystem partners), Salesforce has consistently risen to the requirements in the industry to allow revenue teams to manage the customer journey from first engagement to mutual commitment in the form of “closed/won” and beyond.

Much has been said about the importance of data hygiene and accuracy which is the oxygen in the blood of that CRM heart. Naturally, most conversations around data hygiene have centered on data pertaining to contacts, and not so much about account data– from educating the reps on keeping their share of data clean and complete, to demand generation and marketing operations teams using integrations and data vendors to supplement these efforts.

Lead Scoring Alone Can’t Do All the Heavy Lifting

Lead scoring has long been established as a practice that helps direct your reps to the leads most likely to close fastest — and let’s face it, that’s really what it’s all about. The lead scoring practice is rooted primarily in contact behavior and to some degree, technographic and firmographic aspects of the contact.

As account-based marketing has increasingly gained acceptance, revenue, and marketing teams have struggled to parlay their best lead scoring practices into productive ABM practices.

Some challenge areas include:

• Lead scoring models today are premised on the completeness of data and levels of engagement at the prospect (lead or contact) level with little or no regard to account-level data and overall fit of the target account to the ideal customer profile.
• Segmentation is done mostly on broader account firmographics, like employee size, revenue, category, and occasionally technographics. In other words, go-to-market teams tend to segment on what’s readily available.
• Intent data promises to indicate pent-up demand without really refining or improving segmentation and without surfacing accounts you should be targeting to create demand for your product. Like behavioral lead scoring, intent data tends to be a lagging indicator.

This currently established approach to segmentation and scoring does little to enable personalization in your messaging, and table stakes for today’s go-to-market motions. It also tends to mean that you’re waiting for prospects to reach out to you instead of pro-actively identifying and engaging in accounts that are a good fit for your product, and most likely need it, whether they know it yet or not.

This is especially true when selling and marketing to small to mid-sized businesses (SMBs). SMB buyers expect personalized buying experiences that speak to their specific business needs and circumstances. Moreover, SMB prospecting — being a volume play — has a much higher magnitude of wasted efforts and resources if not managed well within the CRMs.

Most existing databases are backwards focused, in essence, your database is who you use to sell to, and based on what you used to sell, a large part of that may be irrelevant to your upcoming annual revenue plans.

An account-first approach that leads with account identification, classification, scoring, and prioritization makes better use of your resources and is more compatible with account-based marketing programs.

An account-first approach starts with reporting on your funnel only in terms of unique accounts per stage, rather than unique leads. For example, two MQLs from Acme Corporation would count as a single account-first aMQL from Acme Corporation. (Salesforce Lightning’s ‘count unique’ feature makes this easy as pie.)

Three contacts in your CRM who are all on the buying council for a single opportunity with Acme Corporation might count as three SQLs in your old demand gen funnel but really count as a single SQL in a modern account-first funnel. (After all, if you have 3 SQLs from a single account for 1 deal from that account, your Closed/Won ratio should be 100%, not 33%)

All this readily translates to identifying marketing qualified accounts (MQA) within your account-based marketing programs. For example, we use minimum thresholds on average Pardot score and total Pardot score for all leads or contacts associated with an account to qualify an account as an MQA. This helps avoid disconnects between accounts you rate as an MQA and the actual behaviors of associated prospects.

Account-first Continues with Account Scoring

Account scoring is the process of sorting all the potential customers in rank order from the most to the least valuable. The estimated value of an account is equal to its proximity to the ideal customer profile.

“That sounds like lead scoring,” you might say. It’s similar in the sense that it’s scoring. But your scoring is not on the lagging basis of lead behavior but on the basis of an overall comparison of the picture of a given account to the picture of your ideal customer profile. Naturally, you can score on the classic firmographic and technographic parameters, but with platforms like BuzzBoard, you can extend that scoring model to include any number of some 6,400+ signals per account that draw on the target company’s digital footprint.

Account-first and account scoring means getting your Salesforce org ‘account’ object in order first, so you don’t spend time and money enriching and updating lead records for off-target accounts. And so you don’t spend valuable SDR and AE resources calling-down least-fit accounts. It means generating the most accurate, most representative picture of your total addressable market that you’ve ever had, or have ever reported upwards to management.

Investing in your account records first will keep you focused on the richest target accounts — those most likely to close the fastest — and help shape and improve your individual prospect database.

You can also segment your accounts by score to align go-to-market investment to resources. For example, you may decide to NOT invest resources in the lowest scoring quartile of your TAM. For the second-lowest quartile, you may, for example, limit yourself to e-mail marketing, and reserve full-on account-based marketing programs for the top two quartiles.

We have customers and prospects tell us time and again that they want to take the “I feel” gut decisions out of their go-to-market motions. Shifting to an account-first and account scoring model introduces data-driven, bias-free, decision-making in the allocation of scarce resources.

Generally, our customers ask us to provide a refined score to their Salesforce org, through our API integration. Some customers, who want to integrate pre-existing data they have stored in their Salesforce org, ask us to provide via the API a handful of unique data signals that are the best indicators of ICP fit, and they then calculate a fit score at the account object level in Salesforce.

“We see the data, and the signals locked in the data, as the enabler for greater sales efficiencies through account scoring and prioritization, and as the enabler for building a highly accurate ICP, and then scoring accounts against it,” Stephane Gringer, Partner at Chameleon Collective said. “Rich signal sets that go beyond basic firmographic and technographics are key to building go-to-market activities uniquely tailored to the organization.”

BuzzBoard’s scoring algorithms leverage both machine learning and AI-driven analysis. The algorithms can be customized to the context of a specific enterprise or product or service. And it may be used in conjunction with other filters, such as selected technology groups.

The final score for each account, recorded with each account record in Salesforce, can then be used, for example, to prioritize outbound activities by SDRs or AEs. This is incredibly valuable for organizations that have far more target accounts in their CRM than they can adequately service with their SDR team.

Combining account scoring with our highly granular industry micro-classification system further enables you to build, for example, highly segmented and ranked account audience lists to push into digital ad platforms, with targeted creatives and offers.

And, to bring it all back around to personalization, the wealth of data available allows you to prioritize and highly personalize outbound e-mail campaigns with messages and data points that resonate. (The rankings and personalization can also help you build highly effective inbound chatbot playbooks and website personalization plays.)

The CRM remains the heart and soul of your go-to-market organization. By evolving and expanding your use of the CRM to more efficiently allocate your resources — which are always, ultimately, finite — you breathe more oxygen into your organization’s heartbeat.

Want to start cleaning up your data? Check out BuzzBoard on the AppExchange.