Restaurantology Blog

Defining data decay: understanding the gradual erosion of CRM data quality

July 10, 2023 | Trends and Advice | by Grant Gadoci

This blog kicks off a 3-part series designed to help companies targeting the restaurant industry better understand, diagnose, and ultimately resolve CRM data decay.

While the value of any CRM lies in its customer relationship management capabilities, the quality and reliability of the data it holds are equally crucial.

Buf it you ask anyone with Salesforce access who sells products or services to the restaurant industry for an opinion on the state of their market data, you’ll get an onslaught of pain and emotion mixed with frustration and outright contempt.

Why?

Let’s start unraveling the enigmatic concept of CRM data decay.

The perils of dark data

Anything that is underused or neglected over time will gradually decline in effectiveness. This is as true for muscles as it is for data.

Data decay, also known as dark data, refers to the gradual degradation of data quality over time. It manifests as the accumulation of inaccurate, incomplete, or outdated information within a CRM. As data deteriorates, unstructured or untagged fields emerge, remaining untapped when generating reports and dashboards in the CRM.

Frustratingly, data decay poses a range of negative impacts on businesses, and is ascribed to a variety of factors.

Finding the causes of data decay

While businesses continuously collect market information, real-world dynamics ensure that data can quickly become obsolete or unreliable.

Diagnosing the root cause of CRM data decay often reveals two key factors:

  1. the (in)stability of the underlying market, and
  2. manual updates as a primary strategy for data acquisition.

Selling to the restaurant industry means navigating an industry that falls somewhere between transient and turbulent on the volatility spectrum. With market conditions prone to sudden changes, keeping numerous CRM fields updated over time can feel futile.

It’s also important to remember that a CRM’s default data acquisition strategy relies on manual user entry, which clashes with the ever-changing nature of the industry. The probability of consistent field updates made by fast-paced, goal-focused sales reps over time, when expressed as a percentage and rounded to the nearest whole number, is 0%.

This combination of a rapidly shifting industry and sporadic manual updates leads to what is known as static CRM data—information that remains unchanged over time and is often stored in its original format, typically free text. Unfortunately, static data no longer reflects the present reality and can perpetuate a self-fulfilling prophecy of bad data.

Data accuracy of manual user entry over time

The curse of data decay on sales prospecting

Data decay poses immediate and debilitating concerns for businesses reliant on market intelligence for outbound sales efforts. Two prominent problems arise:

  1. Short-term handicapping: With large portions of data left in the dark, decision-making becomes sluggish, leading to unknowingly deprioritized or missed Ideal Customer Profile (ICP) accounts, uncharted competitive landscapes, and painful, inequitable territory generation. Operationalization of data comes to a grinding halt.
  2. Long-term scaling difficulty: Scaling the organization becomes challenging as sales reps and Revenue Operations (RevOps) struggle to find ICP accounts consistently, especially when the underlying industry data fluctuates. Companies often respond to decreased market visibility with increased headcount, straining financial resources. Silos of localized knowledge are created, exacerbated by employee turnover.

These issues—poorly operationalized data, scaling difficulties, and ultimately, poor CRM adoption—can inflict significant financial losses.

Data decay is costing you money

Stale data lurking within a CRM system can have far-reaching consequences, undermining various aspects of business operations.

At its core, bad data is time consuming and expensive. And the simple act of allowing data to stagnate can have severe repercussions on a business, including:

  1. Impaired decision-making: Outdated or incomplete information hampers the ability to make informed decisions, hindering sales, marketing, and customer service efforts. Without accurate insights, businesses struggle to identify opportunities or tailor strategies to customer needs.
  2. Wasted resources that increase costs: Pursuing leads based on stale data wastes time, energy, and resources. Efforts are diverted away from high-value prospects, resulting in poor return on investment.
  3. Lost revenue via funnel thinning: Inaccurate or outdated data hinders lead generation efforts, leading to slower lead conversion and a lighter downstream revenue.
  4. Delayed revenue: Poor data hygiene causes speed-to-market delays, negatively impacting product launches, go-to-market strategies, and time-sensitive campaigns, translating directly into financial losses.

By recognizing the cohesive impact of impaired decision-making, wasted resources, funnel thinning, and delayed launches, businesses gain a deeper understanding of the urgency to combat CRM data decay. Embracing data freshness practices not only ensures accurate insights but also streamlines operations, maximizes resource allocation, and positions businesses for success in a dynamic market.

Conclusion

Much like atrophy, data decay varies in both severity and impact. To navigate the rapidly changing data ecosystem, businesses must adapt quickly, maintaining their B2B marketing and sales data by mitigating rapid data decay. In the next two blogs in this series, we’ll present a step-by-step guide to assess the extent of data decay and propose a solution to fixing dark data at its source. Stay tuned for valuable insights to revitalize your CRM data.