A customer data platform is software that collects customer data and events from different sources, unifies that data, keeps history of that data, and constructs a full profile with all possible properties/traits on the customer. These properties can then be shared with other apps and tools in your ecosystem.
Wikipedia stipulates a customer data platform (CDP) to hold following commonalities across various brands:
CDPs holds customer data. This customer data comes in the form of first-party or third-party data.
With first-party data, data is collected by a company and only used for that company’s ecosystem. In most cases, you’ll want [as much as possibly only] such data as you’ll know exactly how, when, where, and why you collected the data. Those are important questions to answer when you’re evaluating data accuracy.
CDPs take first-party data in a process called customer data unification. This type of data integration involves combining information from separate sources into a usable customer profile. This will allow you to get the most out of your customer.
Unlike first-party data, third-party data is user data that companies purchase and/or share with other businesses. Since in most of the cases, in complying to common privacy regulations, you need to hold a data processing agreement with your customer, third-party data is seldom regarded as legally useful.
Third-party data is most often used to target new potential users for advertising, to personalize websites for net new visitors, and to monetize apps without another revenue stream. Given how often third-party data changes hands, it’s hard to determine if it was collected with proper user consent.
journy.io only processes consented first-party customer data, enriched with also-consented public data-sets from public forums.
Using a CDP to unify, enrich and share customer data across your ecosystem, has the advantage of:
To see such benefits in action, you can sign up for the freemium version here: https://system.journy.io/register
Changing the way you do business, case by case.
Detect which signups are most likely to buy. Sell more with less effort.
Automatically surface product qualified leads.
Prioritize PQLs call lists and engage with quick actions.
Add tasks and full PQL context to existing CRM and other engagement tools.
Automated sales playbooks and collaborative inbox.
Onboard. Monitor. Get expansion signals. Reduce churn, proactively.
Automatically detect churn & expansion candidates.
Accelerate onboarding and product adoption.
Align activities around 360° customer view, with health and onboarding scores.
Automated CS playbooks and collaborative inbox.
Build revenue workflows, based on how people use your product.
Use machine learning to uncover new sales opps.
Add slow accounts to nurturing campaigns.
Optimize engagement playbooks for maximum conversion.
Leverage any data without needing engineering.
See which impact your product features have on revenue, expansion and churn.
Analyse feature importance, usage and impact.
Build key product metrics without SQL, nor coding.
Easily create customer segments based on any product interaction.
Comply to GDPR and CCPA.
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