Wondering how to clean data, when to do data cleansing, and how often you should clean data can make a B2B data aggregator pass sleepless nights. Clean data provides the foundation for all advanced data usage like transactions and analytics. And the data in aggregator databases require regular cleansing and enrichment to keep it comprehensive, accurate, and up to date. Selling dirty data can quickly demolish a data aggregator’s credibility and severely affect businesses that purchase such data. This is whyB2B database quality management depends heavily on periodic or spring cleaning of data.
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Why does spring-cleaning your B2B data matter?
Salable data is a valued asset for B2B data aggregators. However, this asset is subject to constant change. It is seasonal and volatile too. Managing B2B databases is a demanding task for aggregators. Profile details from company contact to addresses, and boards of directors, keep changing. So, relatedB2B databases also need to be updated. Studies show significant quantities of information collected by aggregators decay at a rate of 20% per year and lose validity.
This makes it imperative for aggregators to strive relentlessly to cleanse and maintain their B2B databases. Additionally, growing digitalization brings its own share of opportunities and challenges. Managing enormously growing volumes of data is one of them. With data volumes expected to surpass 163 zettabytes globally by 2025, data aggregators are justifiably concerned about the workload.
Unfortunately, data cleansing and enrichment is a task that many aggregators put off until the last moment. Many of them fear that the volume of data is growing faster than their ability to keep up, and the effort isn’t worth it unless a purchaser arrives asking for a specific dataset. Then, a last-minute sprucing up is done before sale.
Though cleansing and updating databases require diligent efforts and eat up time needed for more pressing tasks– avoiding the tasks is harmful for data aggregators. Regular data cleansing helps B2B data aggregators respond quickly to client demands and with reliable data.
Benefits of clean data
Comprehensive, accurate, and up-to-date data is the main USP ofB2B data-selling companies. It is their tool for effective revenue generation. Clean data provides actionable leads and reliable insights into consumer trends and behavior patterns.
Clean data is a mandatory building block for planning and executing strategies for the end clients of data aggregators. Moreover, dirty data prevents them from gaining actionable analytic insights.
Aggregators who understand the value of integrating, cleansing, managing, and archiving their data to make it salable have an advantage over other aggregators. By recognizing the importance of data consolidation and data integrity, aggregators can transform their data into a valued asset.
For aggregators, it is a sound business decision to not wait for spring to clean their databases and instead get a specialist to do it for them.
How to Spring Clean Your Data
Like spring cleaning your house or office, cleansing aggregated B2B data can seem to be a cumbersome task that diverts the aggregator from the primary task of marketing and selling databases and connecting with customers.
1. “Why” you are scrubbing the database–
Your team must understand “Why” you are scrubbing the database. Explain to them that lead databases or customer records need continuous care, or they end up like drawers full of perfectly folded clothes – but which don’t fit anymore. For example, you may find “Hitech iSolutions” and “Hitech” and “Hitech Digital” all appear in a B2B database regarding the name of the same company. Ensure that you have the latest valid data in your current database and the rest archived properly for past references. Tie data cleansing activities to clear and tangible benefits.
2. Know from where to start cleansing –
Homeowners typically look at every nook and corner of their closets and rooms to determine which areas need the most attention before they start to clean. Similarly, B2B data aggregators should first profile their data and analyze gaps to identify which data sources, databases, and business initiatives need thorough clean-up.
- Data profiling – This is assessing and summarizing the entire database to find how much of the data is fit for use. It also shows up dirty data that can affect business processes, reduce operational efficiencies, and business initiatives. Data profiling helps aggregators to spot which set of data can be enhanced with minimum effort and sold to clients.
With data scientists spending over 60% of their time cleaning and enriching data, it shows how critical data profiling is for B2B aggregators.
- Gap analysis –
Through data gap analysis, data aggregators compare existing database to client requirements to find what more needs to be added to make the data salable. Gap analysis clarifies what steps need to be taken in terms of validation, verification, enrichment and other data tasks.
3. Deal with missing data –
So now with profiling and gap analysis, you know which data fields to cleanse and which to enrich. It’s time to plug in missing values. It is one of the most critical aspects of data integrity. Missing mobile numbers mean customers are not reachable, and missing surnames could cause misdirected communication. Updating missing information to make B2B data accurate, often depends on external or third-party datasets.
4. Remove duplicates –
Many workers of data aggregators, not tenured enough, may downplay the importance of finding and removing duplicate data. Duplicates create chaos that eventually cost aggregators a lot, ruin brand reputation, and trigger customer distrust.
De-duplication is the process of eliminating excessive copies of records and information. Most B2B aggregators run de-duplication as an inline process which takes care of duplicate entries at the time of data aggregation. Many of them have it constantly running as a background process.
5. Validate existing data –
Though data validation is one of the most important steps in data cleansing, it often receives low attention or priority. Validating the database helps aggregators to have clarity, accuracy, and details of their database and helps to mitigate risks involved in data selling activity.
Validating the database for inaccuracies such as capitalization, abbreviations, and spellings may sound trivial however, they have a significant impact on the overall health of the database. HBR cites bad data, causing losses of about $3 trillion annually in the US. By selling a database without validation to clients, aggregators risk ruining their reputations.
6. Handle structural errors –
Unfamiliar naming conventions, typos, or incorrect capitalizations can prove to be a nightmare for aggregators trying to sell their database to clients. Such errors in a database causes incorrect segmentations, inaccurate customer profiles and imbalances at the time of analysis.
7. Address outliers –
Information that falls considerably outside the normal range is an outlier. Though these outliers are less common, they can derail reports, analysis and company profiles. These outliers happen because of inaccurate data entry or unintentional errors. Data aggregators should not be tempted to ignore or remove these outliersin the first instance. Instead, addressing them to find the correct information is advisable.
The presence of outliers in a B2B database can unveil information for patterns and trends. It may provide a niche or a new area of focus that aggregators can benefit from. Outliers, the result of incorrect data entry, can be removed and should be used as a learning to rectify the data collection process to avoid future mistakes.
8. Data enrichment –
This is the process to bring publicly available additional datapoints together to build information rich customer database. With tons of data points being fed into the B2B database, aggregators can sell data empowering end clients to better qualify leads, craft more personalized messages, and provide better experience to their customers.
Of the several kinds of data enrichment including demographic, firmographic, geographic, behavioral; here are two types of date enrichment that B2B data aggregators leverage more than often.
- Executive level data enrichment –
Executive level data enrichment with Job Function / Department i.e., IT, HR, Finance, or Marketing is the grass root level requirement. Accurate professional profiles help in targeted marketing and messaging.
Secondly, enriching the database with lead prospect’s job level/seniority within the company, whether the prospect is a C-level, executive, director, manager, or an individual contributor also has a major impact on the quality and salability of the database.
Executive level data enrichment is required and hence conducted, more frequently than account level data enrichment.
- Account level data enrichment –
Monitoring Fortune 500 and Fortune 2000 company activities across the web daily, including news articles, company news, social media updates, etc. to generate insights apart from data points including company demographics, technographic, and decision-maker data. It is the prime necessity for conducting account level data enrichment. It helps B2B data selling companies to track opportunities in form organizations with purchasing power.
Omni-channel data sourcing and multi-layered data validation checks made 50 million B2B records comprehensive, accurate and updated for a California-based B2B data aggregator. It empowered the aggregator to enable their clients to tap into competition, uncover startup trends, get company funding data, find new prospects and opportunities etc.
Critical information like revenue, assets, employee size/growth, stock information, sustainability measures, environmental and social corporate initiatives CSR activities; makes it fun and rewarding for the clients by reducing the effort and frustration of prospecting, appear in front of the client at the right time with the right message and offer, and provides insights to build successful, long-standing relationships.
How often should aggregators spring clean their databases
How often should you cleanse your data depends on a variety of factors, and not only the volume of data they hold. The frequency with which data aggregators should conduct data cleanup entirely depends on the kind of databases they have.
- Data on start-ups change frequently. The small office from where they started and succeeded may now be a multimillion-dollar company operating from a business hub, which means a change of address and contact details. Start-up data should have regular and timely cleansing.
- A database of small and medium-size companies may require cleansing as frequently as every 3 to 6 months.
- A database of Fortune 500 companies might not require data cleansing so frequently as a start-up. Such gigantic organizations don’t change their addresses, directors, contact numbers, etc., frequently. Still, it is suggested that aggregators cleanse this database once every year.
That said, if aggregators suspect dirty data is costing them money or negatively affecting their brand or revenue generation efforts; they shosuld hire data cleansing experts for a robust and immediate B2B data maintenance activity.
Make spring cleaning your B2B data, a year-round activity
It would be wonderful if one big session of database spring cleaning was enough to maintain the integrity of your B2B database. However, that’s not the reality. Like the regular cleaning clothes from closets and old newspapers from cupboards, aggregators should perform data cleaning frequently and consistently.
How can aggregators make data cleaning a priority? They should focus on data integrity right from the time they collect organizational data. Everyone knows of this, yet it’s surprising how often it gets overlooked.
Aggregators can also consider working with data cleansing experts capable of supporting just-in-time cleaning. Like agencies that come to do a deep house cleaning before the holidays, a data cleaning partner can do the much-needed data cleanup before you sell your data. They bring to the table a value that your own teams would struggle to provide.
About Author
Snehal Joshi spearheads the business process management vertical at HitechDigital, an integrated data and digital solutions company. Over the last 20 years, he has successfully built and managed a diverse portfolio spanning more than 40 solutions across data processing management, research and analysis and image intelligence. Snehal drives innovation and digitalization across functions, empowering organizations to unlock and unleash the hidden potential of their data.
