From the outside, growing a startup appears relatively straightforward — though never easy. Your customer base expands; you begin to offer new products and services; and your employee headcount grows. But what the rest of the world doesn’t see is the inordinate amount of data you become responsible for, all of which must be collected, managed and secured according to the latest privacy guidelines.
Validity’s State of CRM Data Management 2022 report found that 80% of global CRM users said data is the lifeblood of their company and a key growth driver. The flip side of this? Forty-four percent estimated their company loses more than 10% in annual revenue due to poor quality CRM data. This is something startups simply cannot afford during periods of high growth, especially in today’s turbulent economic climate.
Let’s take a look at the data challenges today’s small businesses are facing and best practices to curate and protect data at scale.
The SMB data landscape
Startups conduct business at a rapid-fire pace that’s constantly and continuously changing. Startup leaders have so many priorities to tackle that data governance can fall by the wayside, and there’s little time to define the data you need to collect and your reasons for collecting and storing it. In the early growth stages, you may start out with a “vanilla” CRM system for simplicity’s sake.
But these systems can quickly become unwieldy and even detrimental to your business. Every time a new data point needs to be collected, attributes are added to the CRM with little to no governance. This can lead to the same data being collected in multiple places, and often inconsistently.
Here’s a real-life example to consider: Imagine your Sales and Support teams want to collect the same attribute about a customer. Because each of them has administrative access to your CRM, they both add the attribute to their respective reference objects (Opportunity + Case). But what happens if this data changes after the sale? One object is updated, and the other is not.
If we magnify that over hundreds of data points across thousands of records, the result is inevitable: data inconsistency and potentially lost revenue. Seventy-five percent of Validity’s survey respondents said duplicate and/or inadequate outreach driven by poor data quality loses their company customers. If the habit of collecting the same data in multiple places is not nipped in the bud, it can snowball out of control, and you’ll need to invest in large data reconciliation efforts down the line.
Privacy by design
With privacy regulations like GDPR and the potential American Data Privacy and Protection Act constantly cropping up, there’s more pressure on SMBs and Fortune 500 companies alike to prioritize consumer privacy and the ethical collection of user data.
A quarter (25%) of respondents to the State of CRM Data Management report said their company’s leadership is aware of data quality issues, but supports no specific data quality initiatives. This is especially concerning with regard to privacy compliance — without best practices in place from the onset to promote the ethical collection and protection of data, startups can leave the door open for hefty fines and potential legal issues down the line.
This is where the attitude of privacy by design comes into play, and it must be baked into products and services from the get go for early and continued success. Startup leaders should build privacy and security controls early on and ensure all departments and employees are aware of and aligned to them. This will prevent massive efforts to retroactively implement controls down the line and safeguard your company from potentially violating privacy regulations.
Don’t worry, it’s not all bad news. By prioritizing data productivity, startups can start off on the right foot. Data productivity can be defined as the increase in team productivity that comes from making data easy to enter, find and update — no matter its source. By removing friction from any process where employees, particularly Sales and Services personnel, interact with CRM data, you can make it more accessible and easier to input. This in turn improves the accuracy, productivity and efficiency of your teams, which directly impacts your bottom line: 96% said accurate CRM data improves their company’s conversion rates.
Putting processes in place early in your organization’s growth ensures those processes scale with the company, as opposed to having admins and team leaders try to retrofit productivity solutions once problems start to arise.
To become more data productive, start by identifying roadblocks to updating your data. Which teams are responsible for keeping data up-to-date? What specific fields or pieces of data are they responsible for? What is the current process for team members to update their data? What challenges do they encounter when doing so?
Once you’ve honed in on these issues, devise a plan to solve each one, like making your CRM simpler to use or automating the steps required to update it. When you’re establishing new data management processes like using a CRM, set expectations for usage, obtaining user feedback, and providing the right training to your teams right away so you can replicate these processes moving forward.
As startups grow, inevitably they’ll want to solidify partnerships that get their products and services in front of new audiences and open up new revenue streams. But one consideration that’s often overlooked is the flow of data between partner platforms.
It’s absolutely crucial for an organization that’s processing or storing customer data to fully understand the impact any system they implement will have on that data. For example, imagine you’ve introduced a sales development platform that reduces friction in the sales process by automating outreach. It’s imperative that you know how and where that data is processed and stored, and more importantly how that’s communicated to customers and other stakeholders.
To maintain a good security and privacy stance, startups must implement privacy statements, a Data Processing Agreement, and maintain a list of sub processors to communicate to customers, prospects, and partners. The earlier these practices are embraced, the more you can foster trust and better work with vendors, partners, and customers alike.
Data best practices, at scale
As your startup grows and evolves, data best practices must be your bedrock. By laying a strong foundation of privacy by design, data productivity, and establishing thoughtful data partnerships early on you can mitigate risk and replicate success as you scale.
The bottom line is, data best practices shouldn’t change as you scale. Instead, what will change is who’s looking after these processes and the rigor with which they’re monitored, managed and executed. For instance, an early stage startup may rely on templates or controls provided within the platform they’re using, like Salesforce’s guides for implementation of GDPR controls. Then, as the business scales, a Privacy and Security team managed by a CISO will take shape, and the responsibility of ensuring compliance will transfer to them.
Eighty-four percent of survey respondents said they use data to differentiate themselves and gain a competitive advantage. If you can prove your organization has an understanding of, and is working toward, the implementation of data controls and best practices, you’ll set your business up for success at any scale.