From the outside, growing a startup seems relatively easy – although it is never easy. Your customer base is growing; you begin offering recent products and services; and the variety of your employees is growing. But what the remainder of the world doesn’t see is the vast amount of data you are responsible for and which should be collected, managed and secured in accordance with the latest privacy guidelines.
Importance State of CRM Data Management 2022 The report found that 80% of CRM users worldwide said data is the lifeblood of their business and a key driver of growth. The other side of this? Forty-four percent estimated that their company was losing greater than 10% of annual revenue as a result of poor CRM data quality. 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 challenges facing small businesses today and best practices for managing and protecting data at scale.
The data landscape of small and medium-sized businesses
Startups do business at a lightning-fast pace that is always changing. Startup leaders have so many priorities to deal with that data management can get sidetracked, leaving little time to define the data that should be collected and the reasons for collecting and storing it. For simplicity, you possibly can start with a “vanilla” CRM system in the early stages of development.
However, these systems can quickly turn into unwieldy and even harmful to your business. Each time a recent data point must be collected, attributes are added to the CRM with little or no management. This can result in the same data being collected in multiple places and often in an inconsistent manner.
Here’s a real-life example to think about: Imagine your sales and support teams wish to collect the same attribute about a customer. Since each of them has administrative access to your CRM, they each add an 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 scale this as much as lots of of data points across hundreds of records, the result is inevitable: data inconsistency and potential lack of revenue. Seventy-five percent of Validity survey respondents said duplication and/or inadequate coverage as a result of poor data quality result in lack of business customers. If the habit of collecting the same data in multiple places is not nipped in the bud, it may get uncontrolled and you will have to take a position in major data reconciliation efforts in the future.
What role will content play as your business scales?
Privacy by design
With privacy regulations like GDPR and the potential US Privacy and Privacy Act continues to emerge, there is greater pressure on each SMBs and Fortune 500 firms to prioritize consumer privacy and the ethical collection of user data.
1 / 4 (25%) of respondents to the State of CRM Data Management report said their company’s leadership is aware of data quality issues but does not support any specific data quality initiatives. This is particularly concerning with respect to privacy compliance – without best practices promoting ethical data collection and protection from the outset, startups may expose themselves to high fines and potential legal problems in the future.
This is where a privacy-by-design approach comes into play and must be incorporated into products and services from the very starting to make sure rapid and lasting success. Startup leaders should implement privacy and security controls early and make sure that all departments and employees are aware of them and comply with them. This will prevent massive efforts to retroactively implement controls and protect your company from potential breaches of privacy regulations.
Data productivity
Don’t worry, it is not all bad news. By prioritizing data productivity, startups can start off on the right foot. Data productivity may be defined as the increase in team productivity that results from making it easier to enter, find, and update data – no matter its source. By removing friction from any process in which employees, especially sales and service employees, interact with CRM data, you possibly can make it more accessible and easier to enter. 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 rate.
Implementing processes early in an organization’s development ensures they scale as the company grows, unlike administrators and team leaders attempting to upgrade productivity solutions when problems begin to arise.
To increase data productivity, start by identifying obstacles to keeping your data updated. Which teams are responsible for updating data? What specific fields or pieces of data are they responsible for? What does the means of updating data for team members currently appear to be? What challenges do they face in doing this?
Once you have got a handle on these issues, develop a plan to deal with each one, such as simplifying your CRM experience or automating the steps required to update it. When you determine recent data management processes, such as using a CRM, set usage expectations, obtain user feedback, and provide appropriate training to your teams straight away so you possibly can replicate these processes in the future.
Data partnerships
As startups grow, they’ll inevitably wish to strengthen partnerships that can expose their products and services to recent audiences and open up recent revenue streams. However, an issue that is often ignored is the flow of data between partner platforms.
For an organization that processes or stores customer data, it is absolutely crucial to totally understand the impact that any system implemented will have on that data. For example, let’s say you introduced a sales development platform that reduces friction in the sales process by automating outreach. It is imperative that you just know how and where this data is processed and stored, and more importantly, the way it is communicated to customers and other stakeholders.
To maintain a good security and privacy posture, startups must implement privacy statements, a Data Processing Agreement and maintain a list of subprocessors to speak with customers, prospects and partners. The sooner these practices are implemented, the higher you possibly can build trust and collaborate with suppliers, partners and customers alike.
Best practices for data at scale
As your startup grows and evolves, data best practices should be at the core. By laying a strong foundation in privacy by design, data productivity, and establishing thoughtful data partnerships early on, you possibly can mitigate risk and replicate success as you scale.
The bottom line is that data best practices should not change as you scale. Instead, what is going to change is who oversees these processes and the rigor with which they are monitored, managed and executed. For example, an early-stage startup may rely on templates or controls available inside the platform it uses, such as Salesforce’s onboarding guides GDPR checks. Then, as the enterprise scales, a privacy and security team led by the CISO will emerge and responsibility for compliance will shift to the CISO.
Eighty-four percent of survey respondents said they use data to distinguish themselves and gain a competitive advantage. If you possibly can exhibit that your organization understands and is working to implement data control principles and best practices, you’ll position your business for success at any scale.