The Role of Bid Optimization Technology in Preventing PPC Performance Issues
In 2019, businesses are investing more in PPC performance marketing than ever before. Advertisers must constantly be on the lookout for ways to improve Adwords performance if they want to stay ahead of the growing competition. There are a lot of changes advertisers can make to improve performance and an equal number of ways to hurt it. PPC managers can no longer afford to experiment with changes and learn from trial and error. They need to invest in strategies that optimize while avoiding performance issues altogether. Automated PPC bidding technology is the key. Here’s why.
1. Quality data insights
Quality data is essential if you want to develop an effective optimization strategy, create accurate forecasts, and make the most of key insights to improve visibility and campaign performance. The better the quality of data you’re able to access and analyze, the more opportunities you’ll have to boost conversions, beat out the competition, and drive revenue from your ads.
One of the biggest reasons for missed goals in PPC performance marketing is low-quality data. Even if you’re using the most advanced optimization techniques, low-quality data can drive misguided decisions, causing PPC performance to fall short of expectations.
Advanced bid optimization technology is uniquely positioned to address this issue by analyzing a unified data set to make profitable bidding decisions. On the basic level, Google’s bid automation technology utilizes bid landscapes, historical performance, and other quality data to drive performance-enhancing insights. Advanced PPC automated bidding tools like QuanticMind by Centro can also consider additional categories of business data, such as offline data from call centers or CRM platforms, data from the web and mobile tracking solutions, inventory systems that track supply constraints, and other contextual data.
By taking advantage of all relevant categories of data, bid optimization technology is able to make informed changes to achieve peak performance. If you rely on a manual strategy or bidding solution that doesn’t capture and leverage all critical data, then you may have some inherent performance issues as well as missed opportunities.
Fully utilizing a unified data set that includes deep funnel metrics will unlock insights into where your prospects are in the sales funnel when you reach them. It can also help you understand which steps in the customer journey are most valuable for your advertising goals. Certain milestones of the customer journey can serve to predict whether a click will lead to a sale, and how much revenue that sale will return. Bid optimization technology is uniquely positioned to make bidding decisions with driving revenue in mind.
2. Accurate automated bids
Manual bidding is no longer a default strategy in PPC performance marketing. Even for smaller accounts with just a few campaigns and ad groups, there are simply too many important factors that impact bidding decisions to be handled manually, including:
- Click volume
- Conversion/revenue data
- Bid landscapes
- Current inventory
- Audience characteristics
These factors are, of course, always changing. In order for PPC managers to avoid performance issues from under or overbidding, they need to constantly recalculate and update their strategy as the bid landscape and other factors change.
Bid optimization technology has advanced algorithms and data processing capabilities that can accurately calculate the best CPC to maximize campaign performance. Through automation, it’s also able to make constant changes to your bids based on the latest data insights. When you make full use of bid automation technology, it’s possible to avoid performance issues that come from outdated or sub-optimum bidding decisions.
Google’s automated bidding features respond to real-time data signals to make changes to your bids on variables such as device, language, operating system, and performance. QuanticMind by Centro can also optimize bids when data is scarce, for example in the case of long-tail keywords with few conversions. The software uses Natural Language Processing (NLP) to estimate the value of long-tail keywords/product groups.
Here’s a breakdown of the data and process used to calculate CPC and minimize wasted ad spend for PPC:
3. Custom goals and metrics
If you’re having performance issues, it could be because you’re optimizing towards the wrong metric. Every business has unique goals they want to prioritize when optimizing their PPC campaigns. In order to measure performance towards a goal, they need to choose the right key performance indicators (KPIs) to track. Most PPC marketers rely on so-called “vanity metrics” such as impressions, clicks, clickthrough rates, and conversions to measure success. But they often fall short of painting a full picture of how your ads are helping your business achieve your goals.
For example, say your main goal is to achieve a monthly return on ad spend (ROAS) of 150%. In this case, you’d want to include revenue as an important KPI to monitor. It would also inform your bidding strategy, as you’d want to bid more on keywords that generate more revenue and less on keywords that generate less revenue. Bid optimization technology can prevent PPC performance issues that arise from targeting the wrong KPIs. With Google Ads, you can select the right bidding strategy based on specific business goals, such as:
- Target ROAS
- Target CPA
- Maximize Conversions
- Enhanced Cost Per Click (eCPC)
Automated bidding automatically considers all-important KPIs for your business goals when making bidding decisions. Third-party bid automation tools can also help you target a wider range of goals based on a hybrid mix of KPIs, such as maximizing profit margin. This ensures you avoid performance issues from optimizing towards metrics that don’t fully reflect your goals.
4. Automated bid adjustments
Bid adjustments are opportunities to optimize targeting by increasing or decreasing bids in certain situations. You can create bid adjustments based on factors like:
- What device someone’s searching from
- Where they’re searching from
- Time of day or day of the week
- Demographic factors
You can also make bid adjustments for certain audiences, such as remarketing lists for search ads (RLSA) or in-market audiences. It’s common for account managers to make bid adjustments manually in PPC performance marketing. This, though, can inadvertently lead to some efficiency and performance issues. A marketer could, for instance, increase bids for mobile devices by 15% because they know conversions are higher on mobile devices. But what if a 10% bid adjustment could achieve the same results? Or what if targeting in-market audiences (who are often searching from mobile anyway) yields better results than a mobile bid adjustment?
The only way to ensure your bids are optimum is through experimentation. But if you automate bid adjustments, machine learning technology can discover the ideal bid changes for you. It can also make constant adjustments to bids to keep up with market fluctuations. The ability to make thousands of granular bid adjustments at scale can significantly reduce wasted ad spend and improve campaign performance overall.
Contrary to popular belief, bid automation technology can be used for a lot more than optimizing keyword bids. Top-of-the-line tools have many features to help you improve Adwords performance, such as advanced reporting and forecasting capabilities.
Google Ads offers internal forecasting features from Keyword Planner so you can see how different keyword targeting and max CPC affect long-term performance. Bid optimization technology can also forecast future performance based on important factors like bidding strategy, historical performance, seasonality, bid landscape, and more.
Accurate, data-fueled forecasting is important if you want to improve Adwords performance and avoid efficiency issues. Most marketers create an initial forecast to secure a budget and plan how to spend it. But as they make changes to their bid policies and targeting strategy down the road, the forecast becomes inaccurate. And even if they don’t make changes, the competitive landscape will shift. So, having an automated, up-to-date forecast at all times is incredibly valuable to avoid performance issues. Any changes you make to your account that inadvertently hurts performance will be instantly visible with forecasting. The forecasting feature available within QuanticMind by Centro allows users to view the predicted performance of bid policies up to 100 days into the future.
6. Anomaly detection
It’s primarily the job of a PPC account manager to ensure that campaign performance keeps up with forecasted projections. If your CPA or other performance metrics vary widely from expectations, then an error in your account or data could be the problem.
Whenever an anomaly occurs, PPC account managers need to act quickly to pause problem campaigns and address the issue before it causes too much damage. This task becomes a problem with PPC automated bidding because bidding algorithms are constantly making changes. They also calculate bids using much larger datasets than what account managers using manual bidding would normally handle.
But there are certain features you can use to automatically detect anomalies and minimize their impact on PPC performance. Google scripts are one option you can use to automate this process. For example, there are scripts that can regularly scan your account performance and automatically email the account manager if statistics vary too far from projections. There are also scripts you can use to automatically pause problem campaigns or ad groups, giving PPC managers time to address the issue.
Effective anomaly detection also involves assessing the quality of low fidelity data and making necessary changes to avoid performance issues based on it. For the most part, more data input is always good, unless it’s low-quality data that keeps performance below peak potential and wastes significant ad spend. Often these data quality issues are hidden in the sub-segments of relevant data, making it difficult for marketers to discover by hand. Advanced bid optimization technology is uniquely positioned to address this issue.
QuanticMind by Centro includes an array of anomaly detection techniques to identify potential data issues. In a complex automated bidding process, anomaly detection is the last check before new bid calculations are pushed to publishers:
It monitors all key metrics, including cost, revenue, clicks, CPC, and more, then compares their daily performance to forecasted expectations. If results vary significantly, the tool automatically prevents bidding from being updated from deviant data and sends out an alert for account managers. Once the potential data issue is solved, bidding is resumed.
The Bottom Line
Bid optimization technology is a powerful tool for improving Adwords performance. But it also has important features that help advertisers avoid problems with their accounts and campaigns. Manually diagnosing PPC performance issues is time-consuming, and account managers may never fully identify the extent of the issues. That’s just one of many reasons why bid automation tools are essential for succeeding with SEM.