Most companies have dirty data—lots of duplicates, incorrect fields, and missing values. This happens because you have data coming into systems from dozens of different sources, like field events and email lists, and there are lots of people in sales and support constantly mucking with your data. It’s garbage in, garbage out, and even the best data can decay in a matter of weeks.
Data cleansing is done through a series of configurable rules that form a data pipeline.
Clean Your Dirty Data, and Keep It that Way
Openprise uses a series of configurable rules to automate your data cleansing efforts to your exact specifications. You can set up rules to continuously monitor your data in applications like Salesforce.com and Marketo to look for changes and clean data in real time. You can:
- Clean up incorrect email and website addresses.
- Fill in missing address parts like city, state, and country.
- Fix capitalization issues – NO MORE SHOUTING AT YOUR PROSPECTS WITH ALL CAPS.
Make Normalized Data the New Normal
Every data provider has its own quirky formats. It’s a recipe for dirty data. Two-letter country codes or country names spelled out? Company size ranges like “1-50” or exact numbers like “53”? This can make reporting a nightmare, and even Excel gurus can spend hundreds of hours a year normalizing incoming data. Openprise provides sets of configurable rules in pre-built “data recipes” to:
- Standardize on company names, such as “GE” vs. “General Electric” using fuzzy matching.
- Normalize phone numbers in every country, based on the right local format.
- Normalize state and country fields to two-letter codes or spelled out, even with data in local languages and double-byte character sets.
No more spreadsheets, no more macros, and no more massive, error-prone filters to normalize your data to get the reports you need. Say good-bye to VLOOKUP and the spinning hour glass.
Openprise includes reference data to normalize key fields.
Openprise lets you deduplicate leads, contacts, and accounts.
Dump Your Duplicates
Duplicate leads, contacts, and accounts can wreak havoc with your lead scoring, muck up your attribution models, and cause multiple sales reps to call on the same accounts. Sophisticated, configurable data cleansing rules ensure you keep the right data. Eliminating duplicates is child’s play for Openprise. It can:
- Employ fuzzy matching to identify dupes.
- Merge leads using best practices to ensure the right information survives in the new record.
- Fully automate, or manually review each recommended change from your data cleansing efforts.
- Customize rules to your company’s unique requirements.
Match Leads & Contacts to Key Accounts
How do you know if the leads you’re generating are coming from the right accounts? Do your field reps know about the leads sent to your inside sales team? Openprise’s pre-configured data recipes can help you:
- Leverage sophisticated algorithms to associate the right lead with the right account
- Create coverage heat maps to show the number of leads delivered in key accounts by job level and job function.
Unlike other solutions, there are no black boxes with Openprise – you can see exactly what’s happening, and make changes to align with your company’s business processes.
Next: Learn about Openprise’s data enrichment capabilities.
Openprise can normalize account names, and then match leads to accounts using fuzzy matching.