Amidst recent widespread privacy changes, the digital advertising industry is also now facing economic disruption. Ad budgets are tightening (an ongoing trend year-on-year), so it’s important now more than ever for marketers to be smart about where their spend is being allocated.
Consumers will be more responsive to brands that remain empathetic, understanding, and reactive to the current sentiment, especially during economic uncertainty. App marketers should take this time as an opportunity to personalise their ads to empathise more closely with the current situation for consumers.
This is an opportunity to explore new ways to engage consumers without always thinking about selling them something, but rather, taking the time to uncover what they are interested in seeing from a brand and, more importantly, what they expect from brands.
Attribution, targeting, and personalisation
Advertising begins and ends with the consumer. It is, therefore, crucial for app marketers to truly understand their customers if their ads are to resonate with them.
Marketers can seek to understand their customers better by unlocking deep insights from their first-party data. By unearthing macro-behavioural insights in their data, app marketers can tailor their ads for each customer, thereby personalising their offering.
To determine which ads resonate best, app marketers can turn to attribution. This is becoming increasingly critical in digital advertising as it provides a better understanding of how specific ads perform. By monitoring consumer interactions with an ad campaign, app marketers can gather valuable insights into where consumers are engaging most, and therefore determine which ads are resonating, and adapt their ad strategy accordingly.
Personalisation and attribution are crucial because ads work best when they address people’s wants, needs, and desires that adhere to their mindset and lifestyle choices at specific moments. By not doing so, brands risk disengagement and even loss of trust with their audience.
This is particularly the case during times of economic uncertainty when brand messaging is all the more critical to resonate with consumers and for marketers to remain conscious of the wider context. Fundamentally, personalisation ensures app marketers can provide a better user experience, enabling them to build stronger, long-term relationships with their customers.
To up-level this, app marketers can turn to machine learning tools to help unlock deep insights with first-party customer data.
Leaving it to the machines
Brands with an app presence have a treasure trove of first-party data they can tap into to help drive insights and a deeper understanding of their customers. They are resulting in better strategies to connect with people on what matters to them, their wants and needs.
Data and machine learning can go a long way in ad targeting. Rather than relying on the traditional persona-based approach, it draws from a brand’s existing first-party data. By implementing tools to automatically measure the relationship between user characteristics and behaviours, app marketers can gather more valuable insights to inform their ad strategy. For example, did an app user click an ad? Install an app? Or use a new app? This all helps to determine the success of a particular ad campaign.
In the best-case scenarios, machine learning will look at a brand’s entire campaign log to understand those relationships and why a campaign performed as it did. This approach eliminates the bias that’s built into personas.
App marketers can be uncomfortable with abandoning the persona-based approach to targeting. But the truth is, that approach was never truly effective in the digital world. And now that third-party data is reducing and privacy restrictions rising, it’s time for marketers to rethink the way they target and acquire their audiences.
By leveraging first-party data, brands can provide a hyper personalised experience based on consumers’ current attitudes and behaviour rather than overly invasive factors such as finances, spending habits and demographics insights alone.
The use of machine learning allows them to target segments of consumers rather than individuals. This way, brands can ensure their ads are still highly relevant and personalised, while remaining sensitive to broader challenges to not appear ‘out of touch’ nor invasive in today’s climate.
Featured image: Cottonbro / Unsplash
