Member Article

Is Your Facebook campaign optimisation hurting your results? Here is how to fix it.

Over the Christmas period, retailers boost their marketing spend across channels in an attempt to convert gift shoppers. For example, for Facebook alone, on average, our retailers increase their ad spend by 186% as they move into the pre-Christmas period. This meant that with activated shoppers and increased budgets combined, retailers saw massive returns on their Facebook spend for the 2017 Christmas period. Yet, many retailers continue to measure the success of these campaigns on website conversions alone. An even greater number of retailers fail to realise the opportunities to fully exploit this enormous influx of in-store sales data generated during the busiest period of the year. So, post all this flurry of activity, now is not the time to slow down, quite the opposite, now is the time for retailers to ramp up.

Most retailers optimise their campaigns against the product and audience data collected via their Facebook pixel and SDKs. However, this merely represents 10% of retailers’ sales data. While advertisers have been able to optimise campaigns successfully against this relatively small data set, it is far more effective to optimise against all their aggregated online and in-store data. When personal identification information (i.e. email or phone number) is collected, this data can be used to measure which Facebook and Instagram campaigns helped drive customers in-store. Furthermore, omnichannel campaigns can be optimised to drive customers towards their preferred method of shopping.

Tech-savvy retailers have already started investigating sophisticated multi-touch attribution solutions to tackle the increasingly complex consumer path to purchase. But even these solutions might not accurately measure the effectiveness of online ad spend on in-store sales. They certainly don’t offer the ability to automatically optimise campaigns against omnichannel data.

Facebook introduced ad formats for retailers to target in-store sales data in June 2016. Since their launch, they have been under-utilised features, despite strong results. In part, this is due to the feature setup requirements. In order to measure in-store return, retailers must pass their in-store data to Facebook. This generates several challenges for retailers; these types of data integrations traditionally come with lengthy internal barriers and approvals related to data privacy, ownership, security etc. Passing data to Facebook requires a considerable investment of scarce technical resources to integrate with Facebook’s ever-changing APIs, not to mention the need to aggregate, cleanse and otherwise process the data to meet Facebook’s specifications. Hence, retailers have been too slow to adopt this highly impactful solution. In launching their offline capabilities, Facebook has relied on dedicated marketing partners to enable omnichannel campaign optimisation. These approved partners help address data security concerns by operating as a data ‘safe haven’ by passing limited, filtered, cleansed in-store data to Facebook for attribution. Partners can then leverage further ‘private’ in-store data along with online data to perform custom optimisation based on top selling products, profit margin, store locations and other retailer-specific information, with not just 10% of sales data, but all of it.

For example, one innovative sports clothing retailer worked with partners to integrate data from its web-enabled cash registers, eReceipt systems, and in-store kiosks to discover that its Facebook and Instagram campaigns are driving hugely significant in-store sales. After initial testing and in response to these results, this retailer is now completely overhauling how it optimises its Facebook and Instagram ad spend. In particular, it was very surprised to learn how big an impact its online ads were actually having on sales in its high street stores and as a result is having to rethink its entire Facebook and Instagram campaign strategy to fully exploit the omnichannel options that are now available.

We’ve long entered the world of ‘big data’, and while companies are quick to purchase insights, they often fail to exploit their own data. There’s a literal goldmine of in-store transaction data sitting in retailers’ CRM, eReceipt or EPOS that can be used to fuel their online campaigns. As retailers stare into the face of rampant store closures and decreasing store traffic, they tend to blame Amazon and growing consumer preferences for online and mobile shopping experiences. In reality, consumers still do the majority of their shopping out in the real world. Shifting consumer expectations in the market requires flexibility and adaptation. Customers haven’t abandoned in-store shopping, they just need retailers to catch up with Amazon in leveraging the data they have to better target customers with relevant products.

Retailers must start optimising their online ad spend for both online and in-store experiences. The good news for the slow-to-adopt is that there is still opportunity to exploit Q4 sales data. Through an approved Facebook partner, like StitcherAds, retailers can retroactively attribute up to 90 day-old sales data, meaning that the intelligence from Christmas sales data isn’t yet lost. In 2018, retailers need to stop optimising their campaigns for online conversions. Instead they need to optimise their Facebook and Instagram campaigns based on the whole of their customer preferences by leveraging all the data and solutions available to them.

This was posted in Bdaily's Members' News section by Declan Kennedy .