When looking at mobile marketing and user acquisition, it is vital to monitor and track all actions from targeting decisions to the early actions of users. Data collection drives pragmatic, data-driven decisions, ensuring optimization of UA activities and increased efficiency.
Mobile marketing aims to attract ROI-positive users with a high lifetime value (LTV): for continued success it is vital to cast a wide net, using multiple networks and publishers, iteratively ranking these publishers to ensure the budget is being allocated to the best sources.
The performance of publishers for your application/campaign is ever-changing, with constant fluctuations in the attraction of users moving through in-app events and monetization funnels. Monitoring multiple campaigns, applications, networks, and publishers is arduous work and this is where technology can be your competitive advantage with enhanced decision making speed through real-time data processing.
The data you are collecting is growing exponentially with every hour of UA activity, but the demand for speed is often driving uninformed decisions within UA teams, relentlessly ‘running after the data’ with multiple tools. This ultimately leads to sub-optimally allocated marketing budgets, damaging progress towards your performance goals due to shortage of time and resources.
Technology comes to the rescue, with AI and automated analytics facilitating 24/7 interpretation of incoming data, providing diagnostics & actionable insights into where to best allocate spend. Performance data from both MMPs and distribution channels, combined with AI & RPA, create a perfect incubator for synergy between the vast amount of real-time data & computational power for informed decision making.
This ultimately allows UA teams to react in real-time to the physiological fluctuations in the performance of each traffic pocket, and gives further provision to block fraudulent installs from untested & untrusted publishers, by ‘connecting the dots’ and finding probabilistic clues such as abnormal patterns in conversion rates or in-app engagement.
Proactivity
Harnessing the power of augmented analytics to process data and automatically highlight issues or opportunities increases your team’s efficiency by freeing time that may then be allocated to creatives, marketing strategy, ideation & execution.
Automating analysis with zero latency to ensure insights are communicated with the UA team in realtime and adjustments are promptly suggested also helps increase engagement in the workforce, as technology becomes the catalyst of their hard work. Augmented analytics doesn’t take over from your workforce, it rather enhances human decision-making.
Looking Forward
Besides collating all accessible data from various sources, consolidating it in one place and providing easily interpretable insights, augmented analytics also leverages AI algorithms to forecast future performance and offer a glimpse of what your business could look like, weeks or months later.
This is crucial to competent risk assessment and decision making, and provides valuable details to communicate with other departments on how the application is performing and whether a steering in your media buy is needed. AI does the heavy lifting so your marketing team can focus on positively affecting results.
Overall, partnering your UA team with AI to analyze data at speed can be a major competitive advantage by:
- allowing higher accuracy with data-driven decisions
- increasing speed of decision making with immediate access to answers & insights
- increasing efficiency – Freeing up time dedicated to creatives & marketing strategy
- enhancing tracking and predictive analytics to accurately portray LTV, providing insights into ways to grow with higher value users
- providing advanced reporting capabilities – allowing you to confidently conclude current performance & feed this back internally or externally
- visualizing at a glance all network & publisher level spend and performance
- ensuring that marketing efforts are being allocated in optimal ways
Transforming your data management model may seem like a time-consuming process, part of a longer-term strategy; but that is not necessarily the case, and now is the time to act. Publishers already harnessing the power of AI & Automation are having an advantage over those who do not have these capabilities; the informed decisions they are making much quicker and the time they are allowing their team outside of daily data collection / processing / interpretation tasks is a major competitive advantage. Delaying the implementation of a technology platform with these capabilities puts weight and pressure on your team, stunting the growth of your applications against other publishers, in a market that gets more aggressive and competitive by the day.
The implementation process is surprisingly more seamless than one may envision: you are most likely already collecting vast amounts of data through attribution partners, mediation platforms and the networks themselves, and that very data may be easily ingested by technology partners equipped with the necessary infrastructure. The correct partner will be able to upload this data & enable machine intelligence capabilities almost instantly with time-saving implications from the day you turn the key.
Training your team can be painless too, with easy-to-use dashboards, visual displays of data interpretation, and a touch of dedicated coaching.
Choosing the correct data partner requires research but you may start by taking a look at Bubbleye’s data automation suite. Utilized and built-upon for nearly 5 years, The Kraken software provides a fully pragmatic and transparent automation suite for mobile user acquisition.
Machine intelligence is constantly evolving to produce actionable insights and to automate daily operations ensuring 24/7 coverage across all geos while safeguarding against fraud. If you haven’t dipped your toes into augmented analytics yet, this is the time.
If you are interested in how technology may unlock a whole new level of efficiency and responsiveness, please reach out.
