Amperity + BigQuery
BigQuery CDP with trusted customer context
Your customer data is in BigQuery. Recognizing the person behind a store purchase, an online account, and a loyalty record can still be difficult. We help connect those records so your teams can make more relevant customer decisions.
Build on your BigQuery investment with Amperity. Resolve fragmented identities, make customer profiles available for analysis, and create audiences for supported marketing destinations.
Request a demoExplore lakehouse demoYour warehouse holds the records. Identity connects the relationship.
A customer who changes email addresses may look like two people. A frequent store shopper may appear new online. When those records stay disconnected, your teams can underestimate customer value or send acquisition messages to existing buyers.
BigQuery gives your data team a foundation for analysis. Amperity adds identity resolution and customer context, helping marketers and analysts work from a more consistent understanding of the relationships behind the data.
Identity ResolutionHow Amperity works with BigQuery
Connect the customer data your team selects
Use an inbound Amperity Bridge to connect selected BigQuery tables. Your data team configures the exchange, listing, and subscriber permissions, then maps the connected tables for Amperity workflows.
Resolve fragmented customer records
Exact identifiers alone can miss someone who uses different emails or incomplete contact details. Amperity combines rules and AI model scoring to evaluate relationships across the sources you provide. Review identity results before using the resulting profiles for customer decisions.
Build audiences and put customer context to work
Use configured purchase history and customer attributes to create segments in Amperity. Your marketers can review audiences and send them to supported destinations. Make selected profile tables available to BigQuery for your analysts through the outbound connection you configure.
BigQuery integrationPlan sharing, storage, and processing separately
Plan BigQuery access alongside Amperity processing, output storage, and audience delivery. Review these layers with your data team to choose a configuration that fits your environment.
Layer or option | What it supports | What to plan for |
|---|---|---|
Inbound BigQuery access | Selected tables connect through BigQuery Sharing and an inbound Bridge. | Configure subscriber permissions, table mappings, and supported data types. |
Outbound profile access | Outbound Bridge uses BigQuery Omni with Amperity outputs in Amazon S3 or Azure Blob Storage. | Confirm supported regions, permissions, and the outbound data path during implementation. |
Amperity storage | Outputs reside in Amazon S3 or Azure Blob Storage. Eligible new tenants may use customer-owned storage. | Confirm cloud, region, and tenant eligibility. Google Cloud Storage is not a documented BYOS option. |
Amperity compute and services | Processing uses Amperity-managed compute by default, with application and activation services managed separately from BigQuery. | Confirm processing requirements, destination access, and activation flows. |
External tables provide access to data held outside BigQuery storage. BigQuery Omni also supports transfers into BigQuery; shared access and data transfer are different operations. Your implementation should identify which occurs at each step, including delivery to marketing tools.
Give BigQuery customer analysis a stronger identity foundation
Recognize value across store and online
Connect available purchase history across channels to understand which customers return, where they shop, and how their relationship develops. Use that context to build audiences based on the value your connected sources reveal.
Keep existing buyers out of acquisition audiences
A buyer under a second identifier can remain in a prospecting audience. Use resolved records to build suppression segments, then review and deliver them to configured advertising destinations.
Make retention messages more relevant
Distinguish a recent buyer from someone whose purchase pattern has changed. Build loyalty, repeat-purchase, and win-back audiences using the history and attributes available to your team.
Give analysts consistent customer relationships
Bring resolved profiles into your BigQuery analysis to evaluate customer behavior across connected sources. Your analysts can use that identity foundation in their own reporting and models, alongside the other data they maintain.
Explore ProfilesSee the lakehouse approach in a demo
Explore our lakehouse demo to see how Amperity approaches customer identity and activation. Then bring your BigQuery use case to a personalized walkthrough, where we can discuss the connection, storage, processing, and destination choices your team needs.
Explore lakehouse demoStart with the customer decision you need to improve
Choose an initial use case and the records needed to support it. We work with your team to assess identity, define the relevant customer attributes, and plan the connections. Confirm access, supported data types, cloud regions, quotas, and refresh schedules before implementation.
Validate profile quality and audience membership before activation. Agree on destination requirements and a measurable baseline so your team can assess the result against the decision you set out to improve.
BigQuery CDP FAQs
Is BigQuery a CDP?
What does a Google Cloud CDP architecture include?
Does our data have to leave BigQuery?
Can Amperity run identity resolution on BigQuery compute?
Can we use Google Cloud Storage for Amperity BYOS?
Can marketers build audiences without writing SQL?
Does a BigQuery CDP make every workflow real time?
Make your BigQuery investment work harder for your customers
Bring us the customer decision your team needs to improve. We will show how resolved identity, useful customer profiles, and reviewed audiences can fit the BigQuery environment you already use.
Request a demo