If your decision making is affected by inconsistent data, our data platforms can cleanse and normalize your database to make sure your data looks and reads the same way across all records.
Challenges In Raw CRM Data
Even if CRM data is up-to-date and accurate, it’s still just data. It provides marketers with as much information about a customer as possible, but doesn’t reach conclusions. Marketers need to use this information to uncover their own insights to effectively reach consumers at the right time, through the right channel and with the right message. We source our data from over 40000 sources like social media, web forms, events, manual uploads and so on.
In many organization, prospecting information is captured through forms in their website. Three different prospects who fall under the same level “Senior Manager” can type his designation as “Sr. Manager”, “Senior Manager and “Senior Mgr”. Without a good data normalization strategy in place, this data will rarely be useful.
Marketers usually generate leads by collecting business cards at popular events. Once these records are uploaded into a CRM or Marketing Automation Platform, normalization errors can easily crop up.
LinkedIn is perhaps the most important source of business data, including information from both companies and their employees. Given the sensitivity of the data, LinkedIn does everything to prevent them from being captured by any crawling or scraping. However, the data that’s entered in profiles are mostly entered manually and requires normalization.
Achieve data normalization across your 360⁰ customer profile
We use machine learning to analyze the data and turn it into standardized and usable attributes – Name, Email, Title, Company, Estimated Revenue, Location, Functional Hierarchy etc. All our existing data is refreshed every 30 days.
With over a decade of human-verified research expertise, no other provider has an extensive background in cleansing, verifying and maintaining data to produce 100% accurate contact and company profiles.
How Can We help?
We Are Global
Since we have a vast experience of dealing with global data across APAC, EMEA, North America and LATAM, our analysts and propreitary tools have what it takes to handle multi-lingual titles, variation and other aspects.
Reduce Duplicate Data
Normalize your data before matching and merging duplicates will make it easier to find the duplicates. We use 1000+ data processing rules and algorithms to help find, merge, and normalize all dupes in your database in real-time.
Improve Lead Scoring
We facilitate lead scoring and thereby boost lead generation. For eg. Since Head-Marketing is the decision maker, you can score them differently than a Marketing Manager. Inconsistent, manual and ad-hoc entries can lead to ineffective scoring and might leave your sales reps frustrated.