How can I access the interface?
Once the integration is complete, your account manager will send you the dashboard URL and your login credentials.
How often are the anomalies in the interface updated?
oolo aggregates, monitors, and updates the dashboard following new data delivery from your mediation/MMP/S3 bucket several times daily. Every day you will receive new alerts on the dashboard under the NEW section.
How many users can login to the interface? How many seats can we have?
We can create separate logins for each member of your team. Each user has their own login credentials and can login simultaneously.
Do all users see the same incidents?
Yes, the dashboard presents the same detected incidents and anomalies to all your users. Having said that, each user can create their own saved pre-filter to be able to only see incidents for their own apps.
How do I see the details of an incident?
A list of the newest incidents detected will appear on the far left of your dashboard screen. We call this sidebar the "Inbox". Click on the incident you are interested in exploring to see all the details.
After clicking through, you will find an in-depth look of the anomaly presented on the right. Here you can see how the anomaly plays out across key metrics within the affected dimension(s).
Can I choose which metrics I want to see?
Yes. We can support special requests for the specific DXs you want to be alerted for each cohort metric. For example, if D0, D1, and D3 ROAS are the most important metrics to you, we can set up the alerting for these specific DXs. This can be done during the onboarding process or through your Customer Success Manager. In lieu of any special requests, oolo will set up D0, D1, D3 by default.
How can I search or filter for specific incidents?
The filters at the top of the Inbox allow you to filter and search for specific incidents by app, ad source, UA channel, date, or alert type. You can also flip to the Monetization or UA tabs to focus your Inbox around those professional purviews.
I saw an incident earlier, but now it seems to have disappeared. What happened?
oolo's alerts are based on the day's data pulls together with updated pulls for yesterday and the two days prior. Because of that, the information is subject to updates, especially if certain networks have data delays. If you no longer see the incident, it’s likely because the data was updated, and upon receiving this new data, the data points were found to be within the expected range and no longer constitute an anomaly.
Where can I see a cohort table view of UA data?
The cohort table view is only available for cohorted metrics: ROAS, ROI, ARPU, and Revenue. For those metrics, you can find the cohort table view on the right side of every graph.
How can I locate the most consequential anomalies?
Using the Inbox (the sidebar on the left of the dashboard screen), you can view all incidents (alerts) sorted by date and impact.
Can I provide feedback on incidents to refine oolo's alerting?
Yes! There are two main ways to influence the incidents and anomalies shown in the dashboard. It's important to note however that such changes are made at the company level, and not the individual user level.
- Change revenue impact thresholds with the help of your account manager. Anything below the customized thresholds will not appear in oolo. For example, you can request to only show incidents with at least a 20% revenue impact on top-level dimensions. Because these changes will affect all users, it's important to make sure all stakeholders are aligned before adjusting alerting sensitivities.
- Provide feedback on the incidents by clicking on the thumbs up/thumbs down icons appearing on the right side above all graphs. This will help us better understand what you like and what you dislike so we can calibrate the alert dispatcher accordingly.
It seems that alerts are not updating. What do I do?
If the anomalies are not up-to-date, then it is likely that there is a data delay from the mediation/MMP or S3 and oolo hasn’t yet received the data needed to generate accurate alerts. If the issue does not resolved within 20 minutes, please contact your account manager.
We've found an anomaly that wasn't picked up by oolo. What should we do?
oolo's alert dispatcher filters out insignificant incidents based on seasonality, fixability, business impact, and other factors. If you are confident in the accuracy of your assessment and believe the anomaly is significant, reach out to your account manager. He/She will strive to address your concerns and provide the necessary support.
How can I share alerts with colleagues?
You have two convenient options for sharing alerts with your colleagues:
- Within each alert, there is a Comment section where you can tag your colleagues and leave a message. They will then get an email notification letting them know about the new comment.
- You can also share the link to the specific alert/metric combination you wish to highlight using the Share button. This way, you can effortlessly share precise incident views and details.
What do the different dots in the metric buttons symbolize?
A blue dot next to a metric indicates that the metric is experiencing a positive anomaly — i.e. the actual value was better than the forecasted range. For most metrics, “positive” will mean that the actual value is above the forecasted range. For specific metrics (e.g. eCPI), however, where a lower value is actually the positive outcome, the dot will be blue if the actual value is below the forecasted range.
A red dot next to a metric indicates that the metric is experiencing a negative anomaly — i.e. the actual value was worse than the forecasted range. For most metrics, “negative” will mean that the actual value was below the forecasted range. For specific metrics (e.g. eCPI), however, where a higher value is actually the negative outcome, the dot will be red if the actual value is above the forecasted range.
A hollow blue/red dot next to a metric indicates that the metric is experiencing a positive/negative anomaly, but that the weight of that anomaly wi not a significant factor in the larger incident.
If a metric doesn’t have a dot next to it, this indicates that the values of this metric are within the forecasted range — i.e. there is no anomaly.
What do the blue and red arrows in the right of metric buttons mean?
When you see the arrows next to a metric, it indicates a significant change in the Share of Voice (SOV) mix for that particular metric. By spotting these arrows, you can easily identify shifts in performance and promptly investigate the reasons behind them.
Why is the metric’s last plot point red on the graph?
If the last value in the graph has a red dot, it indicates that the value is anomalous and is not within the range predicted by oolo.
What is the blue shaded area on the graph?
The blue shaded area in the graph represents the expected value range as predicted by oolo’s machine learning algorithms. If the actual value of the metric falls within the range, the plot point will appear inside the shaded area. If the actual value of the metric falls outside the predicted range, the plot point will appear beyond the shaded area — indicating an anomaly. The boundaries of the forecasted range for any given day can be found with the graph's tooltip.
What do the values shown in the Anomalies list for UA incidents mean?
These values show the vectors of impact. They provide information about the impact of the incident.
SOV is the Share-of-Voice of Spend that the specified set of dimensions accounts for out of the total spend for the app or UA channel. The percentage shown is a calculation of the past 7 days of the dimension set’s average spend divided by the past 7 days' average actual spend for the app or UA channel.
The Spend Δ represents the difference between the actual spend and oolo’s prediction.
The Performance Impact KPI (customizable per account) represents the most significant performance metric for your company (in the example below, it’s D0 ARPU) and the difference in percentage points between the actual value and oolo’s prediction.
What do the values above the graph mean?
- The Quick Overview value (labeled 1 in the image below) shows the specified metric’s value for the App & UA Channel as a whole. This allows you to compare the actual value for the more granular set of dimensions you’re reviewing (Campaign & Geo, for example) to the overall value at the top-level so you can make better informed decisions.
- “Actual” is the actual value of the metric for the date of the alert (i.e. the value of the last day’s plot point on the graph)
- Difference from Prediction is the difference in percentage points between the actual metric value and oolo’s predicted value.
What are the version pins, and from where is this information sourced?
Version pins in oolo refer to the app version updates for both the App Store and Google Play. These pins are displayed within each graph whenever a new version is released.
How many sources/creatives are included in the Top Sources & Creatives table?
The top 50 sources and creatives by Spend and Installs are displayed in the Top Sources & Creatives table. The sources/creatives must reach a minimum of 1% Spend SOV or generate a significant amount of Installs over the past 3 days (for the specific set of dimensions) to be included in the top 50.
Even with trained eyes and applied analytics, some performance issues leave faint footprints. Those issues, subtly expressed as they are, can add up to have a big impact on monetization. oolo is simply invaluable for us to find and fix those issues.
User Acquisition Manager
I've been working with the oolo team for over a year now and it's been a fantastic experience.
Head of Ad Monetization Manager
oolo eliminates manual monitoring and allows us to focus on strategy instead of firefighting.
Director of Growth
oolo's forecasting and anomaly detection is vital to our campaign booking, pacing, and delivery efforts.
Sr. Strategic Planning Manager
With all the hot air and empty promises out there, it’s so powerful to see a product that actually delivers on its claims.
Chief Yield Officer
Since oolo actually understands how monetization works, it only alerts us to real issues. That’s helped simplify our day-to-day tremendously.
Managing Director
As monetization becomes more complex, the need for smart automation and optimization only grows. The combination of oolo's AI and domain expertise puts them in perfect position to answer that need.
Director of Growth
I see oolo as an extension of our team. It gives us another pair of eyes and scans our data - in its entirety - around the clock. That’s helped us unlock a new level of control.
Monetization & Growth Manager
In our first month using oolo, they found more than $20,000 worth of anomalies. We have strong people and processes, but oolo’s really helped us level up our monitoring. It’s so much faster and no longer a manual process. It’s been a real game changer for us.”
CMO
Both innovative and reliable! A must-have for performance monitoring!
Programmatic & SDK ADS Manager
Thanks to oolo, our team is always moving and acting quickly — never wasting time and without missing anything that matters. With UA under the same roof as monetization, oolo has all our monitoring needs covered — so we can spend our days doing rather than digging.
Co-Founder
oolo’s ability to not just detect obvious issues like a 90% drop, but to explain more slippery issues — like those obscured by partially delayed data — is super valuable!
Sr. Director of Product
Before oolo, we were manually checking every KPI for each game, ad type, and platform; a time-consuming and unscalable process. With oolo as our AI-powered “smart assistant”, we gain back hours every day; hours that we're redirecting to new avenues of growth.
Monetization Manager
