We are excited to launch this latest innovation in measurement which our CEO, Brian Krebs describes as “fulfilling our mission to help marketers demand more from their data”.
Additionally, in order to make Polaris more accessible to marketers, we are now offering the Polaris Free Tier so that you can start using MMP 2.0 for free! Sign up today. To learn more, submit a demo request or visit our Polaris product page.
Reliable measurement is at the heart of decision making for the mobile business. As you can see from the diagram above, MMP 2.0 leverages multiple measurement methods (including geo lift testing and MMM), blending them to produce an output (single source of truth) that drives the business processes and delivers superior performance. Our team has worked tirelessly to continue innovating so that we can deliver a solution that:
1. Looks like a MMP so that it is easy to use
2. Fits into your existing UA process to avoid any disruptions or productivity problems
3. Merges the strengths of multiple measurement methods to deliver far superior accuracy than individual methods and MMP 1.0
4. Offers sophisticated algorithms that removes the guesswork and signal conflict by outputting a single source of truth the plugs into your existing business processes
We hope you like Polaris and find it valuable in your quest to achieve higher performance while preserving your budget.
Unfortunately, complexity is no stranger to mobile UA teams. Every week, they have to contend with large data sets that have to be assembled from disparate sources to then sift and analyze the data and coordinate numerous campaigns that involve a broad mix of ad channels. According to Adjust, “the average marketer runs 19 campaigns with 14 different networks“. Of course, this translates into the bulk of the marketer’s day being spent on data management.
Through numerous client conversations, we have confirmed that data management and the avalanche of tedious, manual tasks are major pain points. Many are struggling with reducing their daily time spent on campaign management which is a collection of manual and often repetitive steps that seem to explode with campaign scaling. These steps are ripe for automation and our clients witness that as early as the first 30 days of using our platform. The added bonus is that these tasks can be executed in real-time based on live monitoring of the click stream by our platform. So it never sleeps on the job! This approach liberates the UA team to focus on the higher value aspects of mobile UA such as devising strategies, setting goals and creatively adapting to fresh changes in the market.
Another area that our clients find ripe for automation is the bid and budget optimization process. This is where our platform uses real-time performance monitoring to adjust bids, reallocate budgets from lower to higher performing ad channels and pause campaigns based on pre-defined automation rules and business goals. Once again, all the manual tasks and repetitive checking across different dashboards and spreadsheets are eliminated to free up large blocks of time needed for the higher value tasks that are critical to successfully differentiating from your competitors.
Thanks Joe Kim for posting the great article about the death of performance marketing. We certainly agree that things are changing rapidly in performance marketing/user acquisition but think that it is far from dead. It is actually going through a metamorphosis.
For one, we believe that LTV prediction engines wrapped in automation will save performance UA as real performance and scale are VERY realizable across leading ad channels such as ironSource, Unity Technologies, AppLovin, Vungle and all of the other major SDK networks. When Facebook and Google shift to the new setup (described in Joe’s article), the ability to perform will require any UA team to shift their skill sets to become experts at wielding sophisticated SaaS automation technology like MetricWorks UA Command Center.
Secondly, with a UA automation platform and LTV prediction engine that works seamlessly across all networks, one will be able to quickly and easily predict where the most profitable AND scalable venue is to spend one’s money. Currently, UA teams waste significant amounts of time accomplishing these tasks manually with large error margins. Herein lies a further opportunity to save valuable time, reduce the probability of costly errors and to be agile by responding in real-time to data feeds from the variety of mobile ad channels. This capability becomes even more crucial when teams have shrunk in response to the market changes described in Joe’s article. Once again, it is the skills shift that will be important in order for UA teams to take advantage of these new tools to take their game to the next level.