IN-STORE SALES LINKED BACK TO ONLINE MARKETING

Measuring the impact of online marketing in driving in-store sales.

In today’s retail landscape, businesses often struggle to measure the impact of their online marketing efforts on in-store sales. This challenge is particularly pronounced for high-value products that customers prefer to experience in person before purchasing.

Challenges

  • High Online Advertising Costs: Investing in generic paid search campaigns for categories with high cost-per-click (CPC) can be expensive. While these campaigns may drive significant website traffic and user engagement, linking this activity directly to in-store sales remains difficult.

  • Extended Customer Research Phases: Customers often undertake lengthy research processes before making a purchase, involving multiple online interactions across various devices. This behaviour complicates the attribution of in-store sales to specific online marketing efforts.

  • Limited Online Conversions: For products that are primarily sold in-store, online conversions may be minimal. Justifying the budget for online marketing requires a clear understanding of how these efforts influence offline sales.

Solutions

To address these challenges, we have developed a comprehensive measurement framework that connects online customer behaviour to in-store transactions. Our approach includes:

  • Custom On-Site Event Tracking: Implementing tailored tracking on your website to monitor key pre-purchase actions, providing insights into customer intent and engagement.

  • Cross-Device Usage Integration: Utilising solutions that link customer interactions across multiple devices, offering a cohesive view of the customer journey.

  • Privacy-Friendly Anonymous Identifiers: Employing secure, anonymous identifiers to connect online activities with in-store sales while respecting customer privacy.

  • Multi-Touch Digital Channel Analysis: Evaluating the various online touchpoints that customers engage with throughout their research journey to understand their influence on in-store purchases.

Collaboration

We work closely with internal teams and agencies to deliver store sale attribution. 

  • a graph in a magnifying glass

    Working with CRM teams to define a consistent anonymous identifier, integrating into data feeds and email activity.

  • illustration of an eye

    Working with commerce teams to design custom Google Tag Manager triggers and tags for linking key pre-sale events, capture device IDs and anonymous IDs.

  • newspaper icon

    Data engineering processes to ingest new feeds, capture custom variables, construct a user graph database.

Benefits

  • Accurate Attribution: By linking online interactions to offline sales, you can precisely determine the return on investment (ROI) of your online marketing campaigns.

  • Informed Budget Allocation: Understanding the direct impact of online marketing on in-store sales enables more strategic and justified allocation of marketing budgets.

  • Enhanced Customer Insights: Gaining a comprehensive view of the customer journey allows for more personalised marketing strategies and improved customer experiences.

From guess work to a robust attribution framework for store sales.

Every store purchase can now be linked – via a pseudonymous identifier – to ‘pre-sale conversions’ occurring online and the journeys that led to each of these conversions. This allows us to measure the store transactions that had prior online interactions, and crucially the online interactions these customers are having, so that online marketing activity can be optimised and budgeted appropriately.

There are of course some limits to the extent to which we can connect ‘every’ store conversion. To workaround this, we work closely with CRM teams to implement solutions that widen the opportunity to connect multiple devices to an anonymous id within the user graph.

Measurement & Data Crunching

Salesforce Campaign Manager 360 AWS S3

Marketing Campaign Sources

Meta Ads TikTok Ads Display Video 360

The modules that make
it possible

The following Bright Analytics modules work together to solve in-store attribution.

  • ELT
    • Automated data ingestion
    • User graph maintenance
    • Custom data transformations
  • Semantic Layer
    • Online > Store Revenue KPI
    • Data harmonisation
    • Pre-Sale KPI creation
  • Data Visualisation
    • Store dashboards
    • Online > Offline Path Analysis
    • Automated distribution

FREQUENTLY ASKED QUESTIONS

It will depend on the individual client use case and the information that is available, but the crucial point is that whatever we used it needs to be hashed in such a way as to be unrecognisable. This hashing approach will need to be consistent across all places where this anonymous identifier is being generated.

Each online conversion that a device completes can – usually – be linked to a Cookie ID. This is an anonymous identifier, typically a large number. The key part of the process is the ‘pre-sale’ conversion events where are able to link a Cookie ID to a secondary internal anonymous identifier. With these 2 pieces of information we can connect the offline event to the online events via the shared anonymous internal identifier.

When we are able to see the same anonymous internal identifier across multiple device identifiers, we are able to link and aggregate the online activity associated with the device identifiers to the single internal identifier.

Yes! Once a link is established between the offline conversion and the online device identifiers we can start to examine the historic behaviour and marketing touch-points associated with the online devices. Using GA4 raw data or ad-server data such as CM360 ‘s exposure to conversion data, it’s possible to create a picture of the complete (usual caveats apply) online journey that preceded an offline conversion.

Want to quantify the impact your online marketing is having on store revenues?

Connect with our team today and we can start to explore your use case.

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