Advertising is a crucial component of a successful mobile product – specifically in free-to-play genres – and ensuring that these campaigns are both cost-effective and yeilding positive results can often be challenging.
To shine a light on the topic, product manager at LifeStreet Lily Stoelting, dives into the world of mobile advertising to highlight the importance of being fully transparent in a time when mobile margins may be getting tighter.
Given the ubiquity of smartphone use in daily life (people spend an average of 3 hours and 15 minutes on their phones per day, 88% of which is spent in apps), mobile programmatic campaigns are a powerful tool for brands to engage customers in the mobile-first world.
While countless demand-side platforms (DSPs) extol the value of their machine learning (ML) models to make predictions and target new audience segments, this has propelled a lot of “hand-waving” and misconceptions that advertisers can run programmatic campaigns with a “set it and forget it” approach.
The truth is that a lot of human intervention, logic and strategy goes into building these models and a successful bidding strategy. To this day, however, it’s hard for marketers to understand exactly how a DSP makes a bidding decision because they are either not sharing or glossing over the actual calculation behind a bid.
In today’s economy, where layoffs, budget cuts and shrinking margins are an unavoidable reality, buy-side transparency needs to go beyond sharing the programmatic supply chain. It’s important that platforms also lay bare the bidding logic used in campaigns so that advertisers have more visibility and control of their ad spend – so they can double down on the bidding decisions and strategies that are cost effective and efficient.
What is bidding transparency?
Bidding decisions govern which impressions a DSP wins and how much they are willing to pay for them. Understanding and seeing all the elements used to make a bidding decision is what we mean by ‘bidding transparency.’
In programmatic advertising, a bidding strategy is the combination of elements used by a DSP to determine how much an advertiser bids on an impression opportunity. Depending on the campaign goals and budget, advertisers typically use a combination of bidding strategies to achieve their objectives.
How likely is a user to install an app if we show them this ad? How likely is a user to continue using the app for at least seven days? How likely is a user to make an In-App Purchase (IAP)? To answer these questions, a DSP will combine predictions (the likelihood of an event happening) and make manual bid adjustments to create bidding strategies which are expressed in a bidding formula. Another way to think of a bidding strategy is as a set of rules that control different functions of a bidding formula (i.e., increase or decrease the bid amount based on a specified dimension such as day of week, device type, country, ad size; or controlling the percentage of traffic to bid on).
Transparency in today’s mobile marketplace
Programmatic advertising has come a long way since the early days of “black box” media buying. For some time now, “granular reporting,” like the cost and environment in which programmatic ads are shown, has been table stakes for mobile marketers.
Mobile marketers have also become savvier about programmatic media buying. While the majority of advertisers (56%) still use managed service DSPs, as of 2021, 46% managed their own campaigns via self-serve DSPs. And in 2021, more than half of advertisers (52%) planned to increase their self-serve budgets — versus just the 17% of advertisers that planned to expand their managed service spending.
At LifeStreet, we believe all advertisers should have full transparency of their programmatic campaigns — not just those working with self-serve DSPs. As advertisers seek greater autonomy over their advertising expenditures, we built and launched our new marketing platform, Nero, to meet their needs.
Nero lets advertisers see all components and configurations of a bidding strategy, making it easier to know the impact optimization decisions have on a campaign. It also has the ability to A/B test an infinite number of bidding strategies on small percentages of campaign traffic. By assigning a traffic weight to each bidder – from 0% (no traffic) to 100% (all traffic) – advertisers can limit wasted ad spend and preview the likely outcome of different bidding strategies on campaign performance. This level of transparency makes it easier to test, evaluate and implement the most effective strategies to boost ROAS
How transparency helps advertisers’ bottom line
Advertisers can drive better performance when they have a transparent understanding of their bidding strategies. This degree of understanding fosters greater dialogue and feedback between DSPs and advertisers. Together, they can implement new ideas to remain effective, efficient and competitive in an ever-changing market. Since we launched Nero in May 2022, we’ve seen up to a 12% percent increase in ROAS for our app-to-web advertisers and a 60% increase for our app-to-app advertisers.
Here’s an example to illustrate the combined value of bidding and testing transparency:
You’ve launched a mobile programmatic campaign with a DSP with the goal of driving in-app purchases within 30 days of when a new user downloads your app. After some months of the campaign being live, you realise it’s underperforming on the weekends. You collaborate with your DSP partner and decide to test the impact of lowering bids by 25% on the weekends and also adding previously excluded pockets of inventory to your campaign. Instead of implementing these changes throughout the entire campaign, a more practical approach is to test these changes on a smaller portion of the traffic, say 10%, before applying them across the entire campaign.
Let’s assume that after running this new bidding strategy, you observe an improvement in your campaign’s ROAS. This gives you valuable insight that lowering bids and expanding volume across new inventory sources can help scale. With this supporting data, you can confidently apply this new strategy to your entire campaign and have greater insight on replicating and scaling future campaign performance.
Transparency increases confidence
Programmatic advertising is complex. And in an effort to explain how it works, many DSPs have obfuscated the more technical details of the bidding process. Here are some questions you can ask your DSP to gain a better understanding of the bidding strategies driving your campaigns:
- Can you explain how your bidding algorithms determine the bid amount for each ad impression?
- What are the types of data points used to determine the bid amount?
- What types of predictions are being used to make a bidding decision?
- What are the set of bidding rules that are used to deliver outcomes against specific goals?
- How easy is it to see and set bids for different targeting tactics?
Only once advertisers have a complete understanding of what impressions they’re bidding on, how and why, will they be able to assess a campaign’s growth beyond their initial set of KPIs and say with confidence that they are getting the most out of their money spent.
Edited by Paige Cook
