Your business data is the lifeblood of your company. It supports automated workflows, informs customer service agents every time the phone rings, and advises on decision-making.
Small businesses can also benefit from the emergence of big data by optimizing their company’s data and creating processes to get it up and running. According to Experian, eight in ten companies believe data is one of their most valuable assets.
If your business data is reliable and accurate, everything will run smoothly. But when errors, duplicates, and question marks come up, that’s not so nice. When you can’t trust your business data, problems quickly arise and multiply in all areas of your business.
According to Kissmetrics, companies lose up to 20% of their sales due to poor data quality. As early as 2013, HBR also spoke about the ripple effect of unreliable data as part of “Data’s Credibility Problem”:
“When data is unreliable, managers quickly lose confidence and fall back on their intuition to make decisions, guide their businesses, and execute strategies. For example, they are much more likely to reject important, counter-intuitive implications that arise from big data analyzes. “.”
To get the best results as a data-driven company, here are some of the best practices to strengthen the basics and make your business data as reliable as possible.
9 ways to fix unreliable data and increase accuracy
1. Improve your data foundation.
Data debt – the cost of poor data management in an organization – is a significant concern for many organizations. 36% of organizations say data literacy is critical to keeping their organization future-proof, says Experian.
Making your business data more reliable doesn’t happen by itself: it requires strong frameworks, processes and a data-literate workplace. As early as possible on your business trip, make sure that you:
- A strong CRM system to centralize all contact details
- Processes for organizing and segmenting data
- Integrations between apps
- Formal data literacy programs to train your team
- A clear strategy on how you will use and maintain the data you have collected
Remember the old saying: the best time to plant a tree was 20 years ago, the second best time is now. The same goes for the organization of your data!
2. See where new data is coming from.
Just like reliable data, messy and unreliable data doesn’t happen by accident. There is always a source. To make your business data more reliable, follow the path back to where the data came from.
How is data added to your CRM? Are there any forms or manual imports that cause bad data to clutter your database? Do different team members import conflicting data into different apps in different ways?
3. Optimize forms and data collection channels.
After you’ve determined how new data is getting into your apps, take some time to tweak these data collection channels.
To collect valid and reliable data, make sure these factors apply to every piece of data you collect:
- You actually need to collect the data
- You collect it in a consistent and standardized format between apps
- You have clear permission to collect these based on data protection regulations
- It’s stored and organized in the right app for the right purpose
4. Break down data silos.
One recipe for unreliable data is data silos. A data silo is a collection of data that one department can access and another does not.
The negative effects of data silos are bad news for performance and productivity for any business: they include a lack of transparency, efficiency, collaboration, and trust.
To eliminate data silos, use a centralized CRM between departments, connect data between the apps in your tech stack, and focus on building a culture of collaboration between departments.
5. Segment your data.
Good business data is organized, adds value to your company, and is collected with the explicit permission of users. To better organize your data, segmentation is your friend.
The segmentation can look like labels, tags, list memberships, groups, or other properties that tell you more about each contact and divide your database into clear categories of preferences, demographics, purchase history, and more.
When you integrate your data between apps using Integration Platform as a Service (iPaaS), you can create syncs based on your segments and connect the right data between your apps in two ways.
6. Clean up your databases.
To make your business data more reliable, clean up any messy data ASAP. This means that the following will be repaired or removed:
- Wrong data
- Obsolete data
- Duplicate dates
According to SiriusDecisions, it costs about $ 1 on average to prevent a duplicate, $ 10 to correct a duplicate, and $ 100 to save a duplicate if left untreated.
To avoid duplicates and other bad data, create company-wide standards for data entry and maintenance, then sync data from the most accurate source with your other apps and create a holistic view of your database. It is also valuable to set up and document processes to standardize and verify new data.
7. Connect your apps to integrate data.
The most effective data management strategies connect data between apps. This removes data silos, creates an integrated view of all your data, and syncs up-to-date data in the right places whenever something changes.
The easiest way to achieve high quality data integration is with a zero code iPaaS solution that connects the dots between all of your critical business applications, from your CRM to your email marketing system to customer support software.
8. Create accessible reporting dashboards.
Instead of hiding your data insights in private dashboards, make them transparent to the right people on your team. For many KPIs that means your entire team.
Companies with the most effective and reliable data usually select a limited number of effective KPIs and make them clearly visible in the team.
Not only does this help your team invest in the performance of the company, team, and individual, but it also increases the likelihood that errors and inconsistencies in your data will be detected. * The most reliable data have an eye on it. *
9. Schedule regular maintenance.
Maintaining data quality in your company is not a one-off task: it requires continuous maintenance, cleansing and optimization. If your company has a dedicated operations manager, part of their job may be to monitor and optimize data quality. However, it’s definitely worth making data integrity and literacy part of your corporate DNA – or part of every team member’s day-to-day role.
This means that you are laying the foundation for healthy data to flow into your business and be cleaned up regularly, along with processes to troubleshoot problems and automate integration.
By optimizing data reliability, you can ensure that your business is getting the most accurate results and insights from your database both now and later, as data integrity becomes increasingly important.
With automated two-way syncs between apps, including your CRM and email marketing tools, you’re in the best position to holistically manage your data, conduct regular health checks, and create an updated 360-degree view of your customer data.