Data collaboration: the new best friend for business?

The reason?

Increasing privacy regulations (such as GDPR and CCPA) mean organizations can no longer use the third-party data on which they previously relied. They simultaneously face hurdles around collecting and using (first-party) data from their consumers, who increasingly expect companies to be transparent about how this is deployed and now also have the right to opt-out of providing consent for its use in the first place.

These changes are making it difficult for companies to build an in-depth understanding of their target audiences. The issue is particularly acute within certain sectors; a consumer packaged goods (CPG) company for example is unlikely to have transaction data for its consumers as its products are mainly sold by retailers.

Regulation is driving industry evolution

However, these restrictions are also driving positive change such as the end of dreaded data silos to make consumer data easily accessible on request. Data is regarded as a shared organizational asset, illustrated by chief data officers now reporting to the business or CEO, rather than the IT function.

Organizational goals have become about creating common data ground – an objective that includes cross-brand collaboration so that companies can benefit from what is termed second-party data.

Studies reinforce this; a 2021 Winterberry Research paper showed 81% of US executives and 70% in the UK were either collaborating on data with other companies or intended to do so. Companies recognize that building a 360-degree view of their consumers requires new ways to leverage their first-party data so that they can offer their clients relevant and personalized experiences.

The prerequisites for successful collaboration

To adhere to the data privacy regulations without losing ownership of their first-party data, companies need a dedicated technical environment.

Data clean rooms - safe and neutral spaces that facilitate data collaboration and partnerships to exist without any party having access to the personally identifiable information (PII) of the others’ customers - have emerged to fill this gap. A data clean room also provides privacy controls so data can’t be used inappropriately, while enabling data scientists to leverage data to better plan, activate, and measure across the ecosystem.

Data partnerships call for the coordination of teams from all partners, agencies, technology providers, etc, so that the collaboration delivers tangible benefits. This includes a change management process to navigate the shift in mindset from ‘this is mine’ to ‘this is ours’ in terms of data and its activation.

Data collaboration applications

What can organizations expect from sharing data with other companies?

As an overview, they will benefit from incremental sales, spending efficiency, faster insights and improved measurement capabilities.

Retailers for example can provide brands with advanced marketing insights on their consumers (segmentation by average basket value or cross-basket analysis for example) for relevant media, CRM or coupon campaign targeting. Trade analysis (such as segmentation by retail channel type or seasons) enables brands to better optimize promotions and product assortments, as well as maximize the shopping experience (connected in-store screens for hyper-targeted advertising for example) and facilitate product selections optimized to individual outlet requirements. Operations analysis (including information around product shortages and selling out) allow brands to optimize their supply chain through demand forecasting and demand management; it can also fuel sustainability (via calculations such as the emissions related to item delivery) as well as production and innovation.

In short, data collaboration enables key KPIs to be calculated: customer lifetime value and marketing and trade ROI optimization, along with dynamic budget allocation.

Increasing beer sales with second-party data

Artefact worked with a global beer brand leader wanting to prove that the second-party data from its major supermarket partner was delivering business value. The retailer offers a data clean room solution allowing partners to access loyalty cardholder data (anonymously), resulting in a trusted collaboration environment that enables activities such as deterministic matching between data sources (to prevent targeting the same individual twice), data preparation, data activation and data measurement.

From its product portfolio, the beer company used a challenger brand with low market penetration to determine the impact of second-party data on new customer recruitment and sales uplift. Targeting light, medium and heavy beer drinkers (as identified by the supermarket data) it found that new customers came from the heavy and medium categories, rather than light beer drinkers, as had previously been assumed; the pilot delivered a 32% sales uplift when compared to a traditional conversion campaign (which would have been limited to using the beer brand’s first-party data and audiences built in a walled garden environment), an outcome that also benefited the retailer.

Forward-thinking business decisions

Forrester defines second-party data partnerships as "when a retailer, brand, publisher or marketer gains transparent access to the audience data of another retailer, brand, publisher or marketer for marketing purposes – to their mutual benefit."

Regardless of the regulatory changes that are driving the shift to data collaborations, these previously under-used partnerships can be applied in a range of industries (such as the airline, hospitality and banking sectors), offering significant advantages to all parties involved and delivering better experiences for the consumer.

Entering into one or more collaborations of this nature could be one of the best decisions an organization makes.