In today’s omni-channel world, customers interact with businesses through both online and offline channels. This means that businesses collect data from multiple sources – their website, mobile app, in-store purchases, phone calls, etc. While each dataset provides useful insights individually, combining offline and online data gives you the full picture of your customers and their journey.
Why You Need to Connect Online and Offline Data
Here are some key reasons to integrate your offline and online data:
- Understand the customer journey – By connecting data from website visits, phone inquiries, in-store purchases, you can map out the different touchpoints in the customer journey. This helps identify gaps and opportunities to improve.
- Identify your best customers – Matching online interactions with customer details like name, contact info, purchase history allows you to segment best customers. You can then customize engagement for higher retention.
- Attribute conversions more accurately – With combined data, you can identify which online and offline touchpoints influence conversions. This helps allocate resources to the most effective channels.
- Personalize across channels – A unified customer profile enables consistent personalization across web, email, mobile app, in-store. This improves engagement and satisfaction.
- Enrich analytics insights – Offline data can provide context to help interpret online analytics data better. Especially outside factors like weather, store promotions that influence online activity.
Approaches to Integrate Online and Offline Data
There are several techniques to connect siloed datasets and get a single customer view:
- CRM integration – Sync your CRM system which stores offline data with your digital analytics platforms using APIs. APIs can transfer CRM data to tools like Google Analytics automatically.
- POS integration – If you have a point-of-sale system in stores, integrate it with your analytics platform via APIs. Key data like purchase history and customer info can be transferred.
- Matching based on common attributes – Attributes like name, email, mobile number can be used to match customer data across systems. This provides a linked dataset.
- Using a Customer Data Platform (CDP) – CDPs are purpose-built to create unified customer profiles using data from all systems and channels. A key benefit of CDPs is they maintain universal ID keys for each customer as data is processed.
- Identity resolution services – Companies like LiveRamp and Zeotap offer identity resolution to stitch together disparate data based on probabilistic matching. Useful when you lack unique IDs or common attributes.
Best Practices for Data Integration
Here are some tips to ensure effective integration of offline and online data:
- Plan a phased approach – Start by connecting two systems at a time. Identify key use cases. Expand to include more systems gradually.
- Define clear goals – Define the business objectives you want to achieve through this integration. This will help focus your efforts.
- Involve cross-functional teams – Bring together analytics, IT, operations, and other teams right from planning through execution.
- Map data fields – Map fields across sources to identify gaps. Define common formats, conventions and taxonomies.
- Check data quality – Assess data quality across systems and clean up issues before integrating. Duplicate, outdated or bad data can impact results.
- Test integrations thoroughly – Do extensive testing before rollout to catch any errors in data transfer or transformations.
- Focus on use cases – Prioritize high-value use cases like customer journey analysis rather than just amalgamating data.