It’s become a trend lately for inside sales teams to blame industry challenges and market fluctuations for poor growth. The harsh reality is that internal strategies are primarily to blame – especially when it comes to prospect data.
In this age of a global economy, corporations in developed countries regularly exceed profit growth expectations with trillions of dollars flowing limitlessly across borders.
Despite this, many companies still believe the myth that major industry markets are constantly down and totally unsuited for sustainable business development.
Successful corporations that consistently exceed sales growth projections s have learned the value of clean, accurate prospect data. Meanwhile, others that try to make do with prospect databases that contain data that are 40% inaccurate are trying and failing – and losing $3 trillion each year because of it.
What’s the Problem? Bad Prospect Data
Yes, U.S. companies are actually losing a total of $3 trillion each year from bad data.
65% of companies use inaccurate prospect data to guide their major business decisions which, in turn, causes 40% of all marketing and sales goals to fail.
In addition to low conversions, this bad data also results in:
- Poorly performing email nurture campaigns
- High email bounce rates and spam rates
- Irrelevant personalization strategies
- Failed account-based marketing strategies
- Ineffective and expensive social media retargeting
- Poorly performing post-purchase nurturing to prevent churn
Research shows that only 20% of companies are implementing effective personalization strategies and poor data is to blame. That’s not good because 85% of buyers say they’ll dismiss a brand that doesn’t personalize the first point of contact and 80% of buyers have switched vendors in less than 24 months, citing a poor buying experience.
What Does Bad Prospect Data Look Like?
There’s no argument that companies recognize the importance of accurate data for understanding their audience and designing engagement strategies. 84% of B2B marketers say their teams will spend more attention on data in the next year than they have previously.
Where does all the data come from? Previously, data collection was limited to the prospect data housed in CRM systems. Now, marketers have access to complex structured customer data and even paid data from third-party vendors.
Before fixing bad data through methods like data cleansing, it’s important to understand exactly where data goes wrong:
- Missing data: Blank fields that should contain data
- Inaccurate data: Data entered incorrectly
- Wrong data: Information entered in the wrong field
- Duplicate data: A single contact that inhabits multiple records in the database
- Poor data entry: Typos, misspells, and other variations in spelling
- Outdated data: Changes such as job titles, market share, job roles, phone numbers, etc.
Data collection isn’t a new concept. Prior to the days of web browsing and social media, companies relied on scanner data and surveys. However, today’s influx of digital data has made things a little more complicated and introduced a host of new points of failure that can create costly problems.
Prospect Data Cleansing and Governance are the Solutions
Prospect data governance consumes plenty of resources and takes a lot of time and money to maintain.
Meanwhile, inaccurate prospect data is also a nightmare for inside sales teams who spend 65% of their time researching data and only have a 10% probability of connecting with the right person.
Completely avoiding bad data from a third-party source is virtually impossible. Data management is the only key to keep that data clean.
Luckily, Flobile can verify third-party data for up to 99% accuracy!
Flobile uses an AI-driven system developed by data scientists to close loopholes, purge errors, and ensure businesses are only using the best data to inform their decisions.