Customers research online and buy in-store. Measure the full journey.
Digital marketing drives research and footfall, but your marketing analytics can only attribute the online conversions.
Bright Analytics links online marketing to in-store transactions – so you can measure the true impact of your digital spend.
Challenges
High online advertising costs
Investing in paid search for high-CPC categories drives traffic and engagement, but linking that activity to in-store sales remains difficult.
Extended customer research phases
Customers research across multiple devices over weeks before purchasing. This makes attributing store sales to specific marketing efforts complex.
Limited online conversions
When products sell primarily in-store, online conversion numbers look weak. Justifying digital spend requires understanding how it influences offline sales.
The Hidden Cost
Under-investment in what works
Channels driving store visits get cut because they don’t show online conversions.
Wrong optimisation signals
You’re optimising campaigns for online metrics that don’t reflect real business value.
Gut-feel budgeting
Without attribution data, media planning becomes guesswork instead of strategy.
Solutions
Connect online behaviour to store sales
Link website interactions to in-store transactions using privacy-compliant anonymous identifiers.
Track pre-purchase signals
Custom event tracking captures the research behaviour that predicts store visits – product views, store lookups, price checks.
Cross-device identity resolution
Build a user graph that connects activity across phones, tablets, and desktops to a single customer journey.
Multi-touch attribution
See every digital touchpoint that influenced a store sale – not just the last click, but the full path to purchase.
Key Benefits
Prove digital ROI
Finally show leadership the revenue your online campaigns actually drive.
Optimise for real outcomes
Shift budget to the channels and campaigns that generate store sales, not just clicks.
Justify and protect spend
Data-backed attribution gives you the evidence to defend your media budget.
See the full journey
Understand how customers really research and buy – across devices and channels.
How It Works
Online-to-store attribution isn’t a plug-and-play solution. We work closely with your internal teams to build a measurement framework that fits your data and systems.
CRM integration
We work with your CRM team to define a consistent anonymous identifier that connects online and offline activity.
Custom event tracking
We work with your commerce and analytics teams to implement tracking for key pre-sale behaviours – the signals that predict store visits.
User graph construction
Our data engineering processes ingest your feeds, capture device IDs, and build a cross-device identity graph.
Attribution modelling
We connect store transactions back to online journeys and surface the insights in dashboards your team can act on.
The modules that make it possible
The following Bright Analytics modules work together to solve in-store attribution.
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ELT
- Automated data ingestion
- User graph maintenance
- Custom data transformations
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Semantic Layer
- Online > Store Revenue KPI
- Data harmonisation
- Pre-Sale KPI creation
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Data Visualisation
- Store dashboards
- Online > Offline Path Analysis
- Automated distribution
FREQUENTLY ASKED QUESTIONS
It depends on your setup, but typically a hashed email or loyalty ID that appears in both your CRM and your website tracking. The key is consistency – the same hashing approach everywhere the identifier appears.
When a user completes a trackable action online (like signing up for stock alerts or booking an appointment), we capture their device ID alongside their internal identifier. When they later purchase in-store, we match via the shared identifier.
When we see the same internal identifier across multiple device IDs, we link them in the user graph. All online activity from those devices then rolls up to a single customer view.
Yes. Once we’ve linked a store sale to online devices, we can look back at the full journey – every ad exposure, site visit, and interaction that preceded the purchase. Using GA4 raw data or ad server logs, we build a complete picture of the path to conversion.
At minimum: a store sales feed with your anonymous identifier, and the ability to capture that identifier on your website. The richer your CRM and tracking setup, the more connections we can make.
Find out what your digital spend is really driving.
If you’re selling high-value products in-store but can’t connect the dots to your online marketing, let’s talk. We’ll assess your data setup and show you what’s possible.