In our collective 75 years of operational, Private Equity, and consulting experience, the single biggest factor we have observed in successful revenue transformations has been mastery over the use of commercial data. Without question, when all else is equal, the data-driven sales leader is significantly more effective than their more traditional peers. Your portfolio companies can benefit greatly from the approach described below and accelerate their way through the journey of activating the right commercial data.
Commercial data, properly integrated into revenue operations is a massive accelerant to achieving consistent and predictable growth. The benefits of success in this arena are wide-ranging. First, a data-enabled, dynamic account scoring model will consistently ensure your best accounts and prospects are receiving prioritized attention. Productivity measures will spike as commercial resources are consistently directed at the highest value targets. In addition, a data-centric approach also adds a much more scientific approach to territory design, quota assignments and incentive compensation. It becomes the basis for all commercial decision making.
Almost every operating partner has an objective to ensure their companies grow their top line. Using data more efficiently to drive commercial effectiveness will help to achieve that goal. Despite the rapidly expanding availability of data to the contemporary sales leader, there is still far too much reliance on “tribal knowledge” driving hiring decisions, prospect targeting, account strategy, territory design, and quota assignment. This old habit results in spotty performance characterized by high dispersion in revenue results from quarter to quarter. Board members find this wildly frustrating.
The highest-performing sales leaders are relying on data science to improve decision-making across most aspects of the commercial function; from the strategic commercial resource allocation decisions, down to tactical day-to-day execution-oriented activities. Among those who have yet to commit to a data driven approach, the desire is there, however many are unsure how to begin the data-journey.
How do your portfolio companies obtain, organize and activate the data needed to successfully accelerate revenue acquisition?
Obtaining:
Determine Your Data Requirements
When considering allocating capital to acquire commercial data, one must start with a strong conception of the company’s Ideal Customer Profile (ICP).
Once you have a multi-factor ICP and buy-in from your leadership team that the ICP is on target, you can start considering which data sources will assist in scoring prospects. Your end-goal is to be able to qualify, in a relative manner, account quality for buying potential and probability. Your objective in assessing different data sources is their ability to “fill in the blanks” for as many of the ICP criteria you’ve identified. Also, the data source should provide additional insights on your existing best-fit accounts. An important concept to embrace in your data quest is “data enrichment” (covered in next section).
If you provide a sample set of roughly 20 of your best accounts, your data vendor should be able to provide enrichment examples to show your portfolio companies the value they can add to the Ideal Customer Profile. For instance, 3rd party data vendors should be able to provide the names of software systems clients are using that may be complementary to the product. This would be an example of a technographic characteristic.
Data Providers – Who to choose?
There are two main categories of data providers – the generalist, high volume data vendor and the specialist, industry specific source. Examples of each would be ZoomInfo for the former and Definitive Health for the latter. I would recommend starting from a list of at least three of the most reputable firms in each category.
From a cost perspective, most CFOs prefer relationships where the cost can be spread over a period of time as the data source proves to be accurate and comprehensive.
We do not recommend paying a high up-front fixed cost to acquire data. We highly recommend a more opex-like model. A best practice that works well for many of our clients is challenging the data provider to work with your portfolio company to create a business case that solves for justification dependent upon the target outcomes. Once you are on the same page, you should maintain this ROI model in order to continue to ensure the data expense is justified.
Organizing
The logical starting part to organization of data is your first party data. The quality of this data is paramount. Organizations with poor data quality and maintenance are consistent under-performers with higher turnover. This should be considered in the set of “control what you can control” discipline measures across your portfolio companies.
Configuring the CRM, demand generation and other account data systems correctly will set your revenue leaders and CEOs up for long term success. Adherence to strict usage and quality control is a must. When we hear CROs complain about “garbage-in, garbage-out” data as an excuse to avoid commitment to success on the data journey, we immediately know this is cop out. Low adherence to CRM compliance is a simple matter of discipline and reinforcement. When there is a full funnel view of what activities are working with which types of accounts, commercial approaches can be optimized in real time. When there is no visibility due to poor CRM adherence, this creates an unnecessary, and in our opinion, an unacceptable handicap.
When 3rd party data is on-boarded, there are several key steps:
- De-duplication – this is the process of ensuring there is only one record for every legitimate account.
- Fuzzy-matching – ensures that multiple records which may be deceivingly distinct are merged into one. For example, Automatic Data Process and ADP.
- Data Cleansing – refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty data.
Once these processes have been run, you should have one clean database of 1st and 3rd party Data. This is the source of truth! At this point, 1st party data should be enriched with 3rd party data so you have a more complete and accurate view of your clients and prospects.
- Pattern Recognition: At this point, we use simple regression to identify patterns that exist in different cohorts of accounts. Analyzing your best accounts at scale in order to identify indicative patterns is a critical process. This is the first step of building an ICP tool which has statistical significance. The ICP will now include the traits that we identified in your original focus groups as well as the firmographic and technographic data points added in the enrichment process.
Data enrichment is defined as merging third-party data from an external authoritative source with an existing database of first-party customer data. Sales operations leaders do this to enhance the data they already possess so they can make more informed decisions. All customer data, no matter the source, begins in its raw form.
This puts your portfolio company’s team in a position to score and rank every account relative to the ICP.
Activating the Data
Existing Accounts:
Your portfolio leadership team is now in a position to understand which accounts have the most potential for cross-sell and/or up-sell opportunities. This is the “white space” in the existing book of business. Account teams often do an insufficient job of assessing potential in the book. Utilizing data, your companies can more effectively deploy account management talent to strengthen the base and catalyze growth. There’s an adage in the sales profession which states, “It is 8x easier to increase revenue in existing accounts versus selling something to a prospect”. In our transformation projects, the first wave of revenue acceleration often comes from the base.
Prospects:
Processing the scoring and ranking across the company’s entire prospect base is likely a much larger project. This is also where there is usually the greatest return. Once the prospect base is scored and ranked, there exists a much more scientific, fact-based view of the company’s total addressable market. In addition, salesperson engagement soars as salespeople start to make a high quality effort to engage decision makers. They are now aware, with radical specificity, which accounts have the highest potential and probability to close. These accounts are also most likely to have a successful engagement, better retention and ability to cross-sell product. Sellers will have a deeper understanding not only of the relative quality of a prospect, but they will know WHY the prospect is attractive. This added insight is usually a good indicator of the direction they can take the sales process.
Dynamic updating – when you integrate feedback from demand generation and CRM systems, you can create a dynamic model that continues improving over time. For more information on this concept, please see our team’s white paper on Agile Segmentation.
Never has there been more data available to dramatically improve the effectiveness of your portfolio companies’ commercial teams. The breadth and depth of data available has rapidly increased and the systems used to cleanse, synthesize and organize this data have become more open, accessible and inexpensive. Each and every one of your portfolio companies should consider how adding high quality data to their commercial operations can improve their effectiveness.
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Revenue Vision Partners (RVP) blends over 75 years of REAL revenue leadership experience with hundreds of successful consulting engagements. We were founded to focus on the commercial challenges faced by mid-market organizations in growing their top line.
