What is CDP? and Its high level design
Today we will cover the ,most important stack for any product growth person, that is a Customer data platform, let us look into it.......
What is CDP ?
A single platform into which all the data orchestrated from varied sources is dumped, converted into actionable insights and fetched to relevant platforms to build a more customisable and personalised customer.
Features of CDP:
Unified & Unique Customer Identities
Consistent customer experience: if for a customer we can get a unified view on how we target them(tags for campaigns they respond well to etc, then our communications starts taking shape)
Omnichannel campaign orchestration: imagine designing a customer journey, and your marketing team is able to orchestrate the entire journey via a single platform, basis the needs of different audiences, also, having the ability to manage the cross platform communication
Data democratised : all teams, same view(controllable)
Profitability : removing guesswork out of marketing, good handle on hypothesis and experimentation, lower infra costs as well
Auto segmentation and cohort management
Insights and recommendation engine(AI)
Tech-stack
Below diagram can help us visualise role of CDP in terms of backing technologies it is build upon
A good CDP covers Datalakes, Data warehouse and Marketing tools
CDP Infra
Which effectively means CDI: Customer Data infrastructure, serves following purpose
Data Integration :
input data from mobile to web, in-store to backend systems, payment services to help desks, and even your CRM collected via CDI. Then, CDI makes this data available in whichever tools your teams prefer. Decoupling data collection from vendor implementation, CDI enables your engineers to save time writing individual integrations. Input data is connected to a single implementation
Types of Data Integration :
Consolidation: Take data from various sources and store it in a single location, raw or structured is need basis
Propagation: Propagation is essentially automated copying/pasting of data. The data still lives at the original source location, but there is also a copy of it at the destination.(when less data sources)
Federation: Federation is a form of data virtualisation that takes data from multiple sources and makes it accessible from one central point.To the end user, it looks similar to data consolidation, but the difference is that federation doesn’t ever do any consolidation. Data is kept separate until the end user makes a data request. (big companies who want to control costs)
Most Teams prefer Consolidation, but it can get expensive at scale
Data Governance
Tooling to improve accuracy of data, common data standard across the org(same definition for all data elements across teams), team will still find errors, missing fields, and duplicate information that slip through to production.
Audience Management
Making your data work for you, make it actionable, Audience Management resolves all of your user actions into profiles and allows you to identify what’s most important to each user, like their favorite product categories and average logins per month. It amends those profiles in real-time as customers engage and enables you to deliver consistent and personalized experiences across channels.
CDP benefits for the team ?
CDP is automated, meanwhile manual requires ETL(querying) skills, not all teams have equal level of data literacy
* Product team varies Between Marketing and Analytics
* Data Science team varies between Analytics and Engineering
A good CDP combines input from these, to develop a rich central repo of customer profiles, as the customer comes first, it is the heart of all the departments(unites them all)
Features of a CDP
Omni-channel data collection : Your CDP should enable you to collect first-party data from the following sources:
Website, Mobile, Servers, CRM systems, Email systems, Advertising campaigns, Helpdesks
High-quality data integrations : When it comes to evaluating a CDP’s integrations, quality and ease of use are just as important as quantity. Make sure your CDP offers the following:
The ability to turn on new integrations without needing to add duplicative tracking code or SDKs
A short setup ow and comprehensive documentation per integration, so you can get up and running with new tools faster
An extensive integration catalog across a diverse set of categories (analytics, advertising, email, etc.)
Server-side integration components so you can remove code from your applications
Accurate profile unification : Your CDP should unify customer data without any manual input, An API to programmatically access customer profiles and personalize your on-site and in-app experience
Custom audience segmentation
Advanced data controls :SIngle UI to manage data access and schema
Proven reliability and company trajectory
Rigorous security and privacy practices : SSO and 2 factor Auth
Raw data access : Integrations to data warehouses like Redshift, Postgre, Bigquery etc
Cross-functional utility : helps multiple teams
CDP comparison
Recommendation
Most small or mid sized internet services providers prefer Segment and Rudderstack
Segment has a decent market cap, large number of users and easily to read documentation and community forums
Rudderstack is fast upcoming, more developer friendly, more focused on ML capabilities and predictive modeling
Most promising product in the industry has to be Rudderstack, it has higher quality of client support(smaller clientele than Segment)
For a longer term, building CDP capabilities on top of Snowflake warehouse can yield better moat
ROI of CDP
Core KPIs to measure impact of a CDP
Traffic by source
Visitor to Lead conversion by source
Conversion by lead source
Revenue per lead
CLTV, CAC
Developer productivity
Measuring these post implementation in reference to your past baseline, and along with an active control group
This covers the discussion around, CDP, If you ever planning on getting one or building one, then your truly has used some of the best CDPs in the market, also custom built some for my previous orgs.
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