How does Algorithmic Optimization work?
At the heart of AdLibertas is our algorithmically optimized waterfalls. Much like the bulk of modern stock-trading – we’ve found algorithmic management is much more effective than manual optimization. Through programmatic integrations we can optimize your inventory in a more granular way, bringing forward more competition, pushing your prices higher and increasing the yield of your inventory.
How does algorithmic optimization help?
In short optimization is a perfect problem for computer’s assistance. It combines many layers data (data consolidation), applied against many of decision-points (algorithms) to come up discrete decisions with a single goal (increase earnings). While it’s too in-depth to review all the algorithms we employ here, we’ve included some specific rule-sets in our cascading algorithms in way of example:
- Automatic line item creation & updates: having programmatic abilities to create and manage line items allow us the luxury of not being weighted down by a very complex optimization configuration. Complexity– managed properly– can greatly increase performance.
- Discrepancy Monitoring: Ad serving can generate serving discrepancies that can cause problems. Monitoring this over time is important to ensure you’re not losing impressions (& therefore revenue).
- Graduated allocation ramping: Moving line item-order is risky. Just because a network performed highly, doesn’t mean they deserve all traffic. We gradually ramp in and out line items to reduce the risk of incorrect “point-in-time” metrics.
- Fill rate efficiency monitoring: Low fill rates cause inefficiencies, hurting performance. And while weighed against revenue-contribution we are constantly monitoring efficiency of our serving placements.
- Harmonic Oscillation Production: Low amounts of traffic can skew results. Just because a line item performed well on 2% of your traffic does not mean they deserve first-look on 100%. We place them and slowly ramp up their traffic to reduce risk.
- Market Price Testing: The market fluctuates, so should your pricing strategy. It’s important to dynamically adjust your market pricing to be inline with market appetites.