The phasing out of third-party cookies is a positive step towards increasing consumer trust and improving the online experience.
We’re still constantly interrupted by ‘accept all cookies’ pop-ups, and stalked by ads for things we’ve already bought. The resulting consumer annoyance and brand damage really ought to be a thing of the past; as should the wasting of media spend on targeting audiences who’ve already been penetrated.
However, the shift away from cookies has left marketers asking ‘but what’s next?’.
With a post-cookie world on the horizon, the pressure on ad spend is huge. Marketers simply can’t risk missing the mark with their campaigns, or alienating potential customers. They must rethink their targeting methods, and find a new approach to reaching and influencing the right people. Many advertisers are banking on first-party data – details the company has collected directly from the audience, and which they have permission to use – as the answer, but this isn’t as clear cut as it may seem.
Low on trust, but high on growth
The fact is that cookies have been a really valuable tool for marketers, enabling them to target by interest and demographics, while supporting frequency capping which reduces inefficiencies. Cookie data can be used to track what consumers have done across touchpoints, and drive retargeting. Post-view conversion tracking also relies on cookies – you don’t know it’s ‘mission complete’ without them.
First-party data leans more towards respecting consumers’ privacy, but it has its own challenges. Advantages include the fact that it’s permissioned, and is likely to be better quality and more detailed than data obtained by cookies. This creates the ability to build a direct one-to-one personalised relationship that’s based on trust from the start. Having one piece of seed data, an email address for example, allows advertisers to match someone across multiple publishers. In theory, this should provide better return on advertising spend (ROAS).
However, on its own first-party data has its limitations, such as the difficulties of achieving scale and reach. The less data you have – it might just be an email address – the fewer the matches. Data must be captured in a solid and accurate way, with stringent processes in place to support compliance. Connecting all media partners’ data sets is also a challenge; commercial agreements are needed from each party, which isn’t easy when media plans tend to incorporate more than 10 partners.
When first-party data is combined with contextual data, however, it becomes the seed from which a brand can not only grow its understanding of the individuals it’s targeting, but also identify new untapped, highly relevant audiences.
A layered approach
By overlaying first-party data with sales data, and with information on location and behaviour, marketers can reveal audiences with similar characteristics, interests and household circumstances to those who’ve already bought-in to the brand. In other words, they can expand their target audience to include people who might become a customer in the future.
This enables them to reach the volume and scale required to drive incremental sales, while upholding the need to protect personal information: they will be targeting a cohort, not infringing on individuals’ privacy. The approach can be taken a stage further with the application of predictive modelling to anticipate future needs and desires.
The data this generates will enable marketers to answer questions such as:
· How much is being purchased at SKU, brand and category level?
· Where is it being purchased?
· How big is the opportunity to sell more?
· Who else would purchase?
· Where are they likely to purchase?
· How big is the prospective audience?
Ultimately, this layered and unified approach to consumer targeting will strike the optimal balance between effectiveness and efficiency.
Reduced wastage and strong ROAS
Effectiveness is about driving a high volume of sales: how many products are sold in response to the media you serve. Efficiency relates to whether the amount it costs to be effective is worth the money being spent. Hitting the sweet spot between the two will increase ROAS by up to 20%.
Combining first-party and contextual data allows brands to identify clear sales opportunities, and maximise the media budget by using the optimal mix of channels. For instance, combining sales data and predictive modelling will indicate which geographical areas are ‘low opportunity’ – perhaps because they’re already saturated or the category is in decline – and so advertising there will be a waste.
Unable to continue relying on third-party cookies, marketers must find a new approach to ensure the effective, efficient and safe use of media. While first-party permissioned data won’t resolve all the challenges ahead, it can be leveraged using contextual data and predictive modelling to help marketers make the right decisions and reach their goals with an increasingly scrutinised budget. The ability to achieve accuracy, relevance and scale – without any customer trust issues – will also result in stronger, one-to-one personalised relationships with consumers.
- IRI is a big data, predictive analytics and insights company headquartered in Berkshire, UK.