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.
How do we Collect Data?
SMARTe provides intelligence from over 40000 sources like company websites, events, social media, web forms, events, manual uploads and so on.
How do we Process This Data?
Our records go through multiple stages of verification including testing and validation to remove incorrect, duplicate, stale and unverifiable information.
How Accurate is Our Data?
We use a combination of technology, proprietary tools and human intelligence to ensure that every little data point is as accurate as possible. SMARTe’s master Data is aided by 200+ data analysts who build dictionaries, aliases and taxonomies and rules to create algorithms that validate data on demand to ensure overall quality.
With over a decade of human-verified research expertise, SMARTe can create 100% accurate contact and company profiles by harnessing our extensive background in cleansing, verifying and maintaining data powered by Natural Language Processing and Machine Learning Heuristics. Since we have a vast experience of dealing with global data across APAC, EMEA, North America and LATAM, our analysts and proprietary tools have what it takes to handle multi-lingual titles, aliases, variation and other aspects.