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5 Ways to Fix Data Decay Challenges for Your B2B Business Growth

5 Ways to Fix Data Decay Challenges for Your B2B Business Growth
Data decay negatively impacts your client’s ability to effectively engage with existing and prospective customers, impeding the business growth. It’s imperative for B2B aggregators to implement AI-based tools and future-forward practices to eliminate the risk of data decay.

The online business environment is in a permanently volatile state. CXOs change jobs every hour, companies relocate every other day, mergers take place frequently, and new start-ups are birthed by the minute. And the credibility of B2B database aggregators wither under this unceasing assault.

Market studies peg the decay of customer data across industries at about 30%-40% per year!

Data decay affects decision-making and marketing campaigns of B2B businesses that lean heavily on digital data. Fixing decay and maintaining data hygiene is not an activity which can run in silos. It is a comprehensive end to end process including sourcing integrity, multi-layered validation and authentication, calendared crawls for data verification, data cleansing and data standardization.

Manually conducting this task at the pace at which data becomes obsolete, is impossible. AI and automation offer a more effective solution. Coupled with cloud technology and RPA, AI-based data management prevents ‘fresh but obsolete’ data from reaching end users.

For B2B data aggregators, being trusted as the ultimate source of quality data is as mission critical as maintaining an exhaustive database. Let’s understand some major causes of data decay and the solutions to fix the issues.

What causes data decay

Data decay stems from disconnected or changed phone numbers, inaccurate business addresses and invalid emails. Businesses get sold, mergers happen, and several other shifts compromise the integrity of the data.

6 common causes of data decay

Mushrooming of start-ups: In 2018 alone, 30.2 million start-ups entered the US economy. Such accelerated growth of new start-ups, riding on technology and ease of access to resources, leads to a massive influx of new business data, which is easy to miss.

Mergers & acquisitions: With the exponential increase in business mergers and acquisitions, company identities keep sprouting new avatars. B2B data aggregators have to be on their toes about the permutations and combinations emerging from mergers, acquisitions and other venture collaborations.

Changes in credentials: Everyday, key business decision-makers change designations, addresses, or their jobs.

  • 40% of businesspersons change email addresses every two years
  • 21% of CEOs change email addresses every year
  • 20% of postal addresses change every year
  • 60% job functions change every year

Keeping track of these changes and updating, validating and cleansing your databases accordingly is an arduous task.

Unreliable sources of data: With B2B data aggregators under constant pressure to add volumes at speed, sourcing data from unknown and unreliable places and not cross-referencing tends to backfire. In 9 out of 10 cases, this data can be stale and redundant. Wrong data sources for pre-scheduled auto-updates also mean wrong data updates.

Data hoarding: The ease with which data can be collected and shelved tempts data companies to store unverified data in anticipation of situations where it might come in handy. Though such data has forensic value, efforts to make the old data usable against changed realities rarely match the outcomes.

Inaccurate data & missing data fields: With constant changes in the industry, databases tend to skip on including vital information like financial prospects, annual revenue, or company hierarchy, leading to missing data fields.

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Negative impact of data decay

Negative impact of data decay

Inefficient sales performance: As a B2B company, your entire revenue stream depends on quality data. If you sell outdated data, the company’s overall sales performance will go down. Data decay will affect your ability to market your database. Per Target Marketing, 50-75% of a B2B’s marketing success depends on the accuracy of the data.

Dissatisfied clientele: If remained unchecked and unedited, data will decay. According to Gartner, every month around the world 3% of data undergoes decay. Bad data can cause serious repercussions on your client’s marketing strategies, causing you loss of clients and reputation.

Hampered reputation: According to the 1-10-100 rule, postulated by George Labovitz and Yu Sang Chang, if preventing bad data from entering a database costs $1, then rectifying existing problems costs $10. However, it will cost you $100 if you set about repairing the situation after your clients have already been affected. The real loss is that of goodwill, which can kill your business as a data aggregator.

Financial loss: Fixing data decay requires special resources and time, meaning more money needs to be put into it. For a B2B business, the bigger the database, the costlier it is to maintain. Gartner states that the monthly financial loss caused by data decay is on an average $9.7 million.

How to fix decay of B2B databases – 5 proven ways

1. Ongoing data acquisition

A Californian B2B enterprise strengthened its 50 million records database with help of a robust data management workflow powered by ML algorithms. The multi-sourced data aggregated from a range of sources was then put through a verification, multi-layered validation and update process. The resulting deliverable was the development of a strong database powered by an ongoing acquisition cycle that would update, strengthen and enrich the database at regular intervals.

Read more: An omni-channel data acquisition process builds comprehensive and updated database

Some best practices to ensure a robust and effective data acquisition process:

  • Authentic data sources: Research proper global and local data sources to capture data from trusted and verifiable sources to save maintenance costs and reduce verification timeline.
  • In-time data collection: To prevent data latency and assist in-time data appending, choose trustworthy data sources. AI-based real-time data tracking has eased this.
  • Multi-sourced data capture: Access private data sources like online networking platforms, company surveys etc. along with public sources like the national registry, JOLT, BDS etc.
  • Data capture from obscure sources: Gaining access to obscure information unavailable through common platforms requires a lot of research and digging.
  • Collect structured and unstructured data: Structured data is easy to feed in but raw and unstructured data is also important to add quality and depth to your directory.
  • Set up ongoing data acquisition cycle: Ensure fresh data by scheduling a monthly or weekly data update cycle – through manual sourcing or auto-update.

2. Continuous database update

Using social media intelligence: In a 30-sec video world, everyone is glued to social media to stay relevant. People regularly update their status and profiles on social media platforms like LinkedIn, Facebook, or Instagram. Whether it is a job change or a change in marital status, social media is the first to know. Using these user-generated reporting as a source can actually be more relevant than many third-party data sources.

3. Regular data enrichment

Hitech BPO partnered with a French data aggregator that hosted 14.5 million hospitality records spanning across 60 countries to improve the quality of data. With the help of a data consolidation framework and an automated data cleansing process, Hitech BPO standardized, enriched and validated data fields to increase client’s market value and conversion rates.

Read more: Date cleansing and enrichment enhances performance of hospitality database

Some key steps towards ensuring a strong data enrichment process:

  • Change of address registries: Public registries like NCOA (National Change of Address) are an authentic source to continuously track information.
  • Data hygiene strategy: A strategy including email verification, updating missing fields, eliminating duplicates, deleting obsoletes and scheduling maintenance help avoid data decay.
  • Manage your data silos. Merging data silos and getting rid of multiple storehouses can avoid inaccuracies and data decay issues.
  • Switch from manual to automated tools: Automated data enrichment tools have more benefits than being quicker, simpler, and more accurate, especially for huge databases.

4. Data validation and verification

For a USA-based BFSI data aggregator, Hitech BPO curated and verified the chaotic financial records to build a high quality and integrated database. Through automated data verification and data standardization we delivered a database that was clean, free of inaccuracies and of high quality.

Read more: Financial data verification enhances performance of investment portfolios

Factors to keep in mind during a data verification cycle:

  • Verification at source: An exhaustive verification process before inputting any data in your system will help avoid data decay.
  • Mobile and email validation: Asking data subjects to confirm their email address or verify their mobile number with an OTP is a simple and effective way of data validation.
  • Manual and rule-based validation: A comprehensive data check while the initial data input is underway, serves as an excellent baseline for all future updates and verification procedures.
  • Verify migrated data: When transferring company data to another system, it is important to have a thorough examination of data to see if matches original records.

Technology and smart tooling are the future of B2B database solutions

In a fast-paced and technologically innovative world, automation is the key to decay-resistant databases. Today’s database automation processes run on AI and UI-based features to create user-friendly platforms. These allow even non-coders to manage processes from a single dashboard. Smart tools provide exceptional data management and cleaning experience. Most come pre-equipped with data maintenance algorithms as well as abilities to identify, mix and match data.

UI-based smart tools have the capability of running concurrent multiple tests and verification procedures and can tackle both structured and unstructured data in a cohesive manner. They bring true, hands-free automation to data cleansing, enrichment, validation, verification, segmentation and other processes including updating of databases. On the other hand, script-based automated processes require manual intervention and supervision and lack versatility. Overdependence on programmers for each rule modification makes script-based automation processes less efficient in terms of costs, time and resources.

Data hygiene drives B2B businesses

Data decay is a major impediment for data management businesses. It creates financial loss, reputation loss, and a loss of goodwill. For any B2B business to stay strong in the market, a database that is authentic, fresh, and one-of-a-kind is indispensable. Hence data hygiene management gains precedence over any other data management activity. To avoid data decay, routine cleansing needs to follow a steady and cyclic flow of data updates.

Deploy a fine blend of human intelligence and automated tools for ongoing updates, validations and cleansing of your data. Monitoring every change and every new addition to the current data pool is critical for the growth and success of any B2B enterprise.

Author Snehal Joshi
About Author:

 spearheads the business process management vertical at Hitech BPO, 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.

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