Without quality data, your business could be throwing money out of the window. A recent study suggests that 32% of US companies have inaccurate data. With data quality tools, you can identify the flaws and make the right decision. Unfortunately, finding the best data tools for businesses has always been a challenge. But again, this is an expensive problem to ignore. In this post, we’ll discuss what are data quality tools and where to find them.
DATA QUALITY TOOLS FOR SMBS
If your annual revenue is $2- $50 million, you need a tool that works with your CRM. The best tools will provide insights into analytical decision-making.
Echobot collects data and finds its Filmographics and technographics. Unlike paper field notes, this tool provides true efficiency, reliability, and accuracy. In addition, it eliminates the complexity when streamlining data input. Although it won’t clean your data, it works seamlessly if you need some enrichment.
Tye is designed to streamline your marketing processes. Whether you upload your data from Salesforce, SQL, or any other CRM, Tye will clean it. Apart from that, the tool ensures your data is enriched, personalized, unified, and correct.
Tye will identify any fault entries and duplicates. It also analyzes the result to help you understand customer data. If you’re looking for a simple data standardization tool, Tye is a good fit.
DATA QUALITY TOOLS FOR BIG COMPANIES
Businesses with over 1 billion in annual revenue have complex databases. In this case, you need tools for data integration, data transformation, mapping, conversion, and data warehousing.
Uniserv manages customer data without interrupting the day-to-day running of the business. It’s scalable and you have a team of consultants to help you do the job. Uniserv ensures data quality in any location of your business – local and international. The team will check the data bank at different levels, telephone numbers, and email addresses.
This is an essential tool for cleansing, matching, code-free profiling, and duplication. It’s for companies that want to step into big data. With DataLadder, you connect data from different resources and automate quality checks. And to preserve the uniqueness, you can eliminate duplicate values.
Another feature that makes DataLadder unique is that you can link records across enterprises – from TXT files to apps.
This tool collects raw data from disparate sources and checks for uniqueness, variation, and completeness. Whether the data comes from your computer or the cloud, Tibco Clarity will pull it up and start cleaning it. If you don’t know more about your dataset, you can visualize the trends and patterns. Apart from that, you can create validation rules from all the patterns you’ve identified.
WHAT TO CONSIDER WHEN INVESTING IN A DATA QUALITY MANAGEMENT TOOL
The right data tool can bring a positive impact on your business. For large or complicated datasets, you can outsource the process to a third party. Here is what you should look for:
How easy can you make upgrades down the line? Can the tool keep up as the data sources grow?
Speed and efficiency
Will the tool take manual labor away from the employees? You should not only look at a data quality tool in terms of the IT department. Will other business users need it? Will the tool give faster results than my workers? If your overall business strategy relies on automation, the data cleaning process should be automated. Should you automate your sales process? If it doesn’t make sense, you can get someone to manually clean the data.
Are there any add-ons that can make the price inflate? Does the tool come with a subscription fee? You should pay attention to the data points. The minimum time frame is 3-5 data points. Generally, the data point can include the job title, phone number, company, email address, phone number, etc.
Other considerations when determining the cost include:
How long will your staff take to complete the tasks? If the cost is greater than the tool, then you should purchase it. If you use a virtual assistant, then the cost for data cleaning could be cheaper. If you’re more cautious with the data, you should determine the frequency of cleaning.
If you use virtual assistants, the cost of cleaning could be cheaper.
QUESTIONS TO ASK WHEN ASSESSING YOUR DATA QUALITY
* What is the most common complaint?
* What percentage of data is clean and usable?
* Who’s responsible for data management?
* Can the data be trusted?
WHO ARE THE STAKEHOLDERS WHEN SELECTING A DATA QUALITY TOOL?
If you buy a data quality tool without consulting the stakeholders, you may later realize that the tool is not compatible with the technology. Even if you’re the one who runs the CRM, you should never ignore their input. Some of the stakeholders can be:
Head of marketing
This department is interested in clean data to segment leads in marketing campaigns. The team is concerned with contact data, job titles, and buying preferences. Your CMO will need data:
* To create more personalized emails
* For lead scoring
* To push the business towards customer-centricity
* To fragment customer personas
* To track personas across channels
You need the input of the CMOs because they have a clear idea of what they want to do.
Head of sales
This department is interested in updated data. The team will take data from different sources and use it in their ERP system. And because the figures are as good as the data, they need something they can trust. If the data is faulty, the sales team will keep reviewing it instead of focusing on sales-generating activities.
The department also focuses on customer needs, CRM data, and buying history. You don’t want to bring a data tool that is too complicated for those who are not data-savvy.
Head of IT
The IT team is interested in keeping the systems tidy and clean. They ensure all the fields are correct and fulfill all data requests.
These people may be affected by bad data but don’t play a central role. For example, some marketers may fail to segment customers because they lack specific information. Similarly, the sales team may have a challenge reaching people in their CRM if the phone numbers are incorrect. Such complaints show that you need to work on your data.
Pick your data tool carefully
If you want to get your data right, the above tools will fully cleanse and enrich your database. Keep in mind that each tool has different features, so you should choose the one that addresses your business needs.