What are the drawbacks of manually monitoring and adjusting bids across multiple ad groups or campaigns?

Manually monitoring and adjusting bids across multiple ad groups or campaigns in platforms like Bing Ads can be highly time-consuming and prone to inefficiencies. Here are some key drawbacks of this approach:

1. Time-Consuming and Labor-Intensive
Drawback: Manually managing bids for multiple ad groups or campaigns requires constant attention to each individual keyword and campaign performance. As the number of campaigns and ad groups increases, the complexity and time investment required to monitor and adjust each one also grows.

Example: If an advertiser is running 10 or 20 campaigns with multiple ad groups, manually reviewing the performance of each keyword, adjusting bids for underperforming terms, and reacting to competitor activity becomes a massive undertaking that is hard to sustain over time.

2. Limited Scalability
Drawback: As campaigns grow and more ad groups or keywords are added, manual bid management becomes increasingly difficult to scale. It's much harder to maintain a high level of performance across all ad groups when you have to check and adjust bids for each one individually.

Example: An e-commerce business with hundreds of products and campaigns may find it nearly impossible to manually optimize every ad group in real time. This could lead to missed opportunities or inefficiencies in campaign performance.

3. Risk of Human Error
Drawback: Human error is a major risk when manually adjusting bids. Even experienced marketers can make mistakes, such as applying incorrect bid adjustments, overlooking important trends, or failing to adjust bids promptly.

Example: A marketer might mistakenly increase the bid on an underperforming keyword or forget to adjust a bid when market conditions change, leading to over-spending or under-delivery of impressions.

4. Delayed Response to Market Changes
Drawback: Manual adjustments are typically slower than automated systems, meaning that bids may not be adjusted quickly enough to capitalize on sudden market changes. Competitor activity, changes in user behavior, or shifts in demand can require fast bid adjustments, but manual monitoring doesn't provide the speed needed to stay competitive.

Example: If a competitor launches a major campaign targeting the same keywords, a manual bidding approach may not respond quickly enough to adjust bids in real time, causing the advertiser to lose out on valuable impressions.

5. Inability to Leverage Real-Time Data
Drawback: Manually adjusting bids makes it difficult to react to real-time data. With automated systems, bids are adjusted based on real-time performance metrics (such as clicks, conversions, or impressions), allowing for more precise optimization. Manual bid management, however, often relies on periodic reviews and adjustments, which means the campaign may not be optimized immediately based on new performance data.

Example: An advertiser might not adjust bids based on hourly or daily performance data unless they are actively checking the campaigns. Automated systems, on the other hand, can adjust bids on the fly based on real-time fluctuations in performance.

6. Inconsistent Bid Adjustments
Drawback: Manual bid management increases the likelihood of inconsistent bid adjustments across campaigns. For example, one ad group might be overbid while another underbid due to a lack of centralized oversight. It can be difficult to maintain a consistent bidding strategy when adjusting bids manually for a large number of campaigns.

Example: A marketer might bid aggressively on one set of keywords in a campaign while neglecting another keyword set that could drive more conversions, leading to inefficiencies in the overall campaign strategy.

7. Complexity in Handling Multiple Factors
Drawback: In a platform like Bing Ads, several factors influence bid adjustments, including device type, geographic location, time of day, audience segments, and more. Manually managing these factors across multiple ad groups and campaigns can lead to misaligned strategies and suboptimal performance.

Example: A marketer might forget to account for a dayparting strategy (adjusting bids based on time of day) or geographic bid adjustments, resulting in missed opportunities during high-traffic hours or in key locations.

8. Difficulty in Maintaining Optimization Across Campaigns
Drawback: As campaigns evolve, it becomes harder to maintain bid optimization across multiple ad groups. Changes in strategy, new keywords, and shifting goals can make it tough to track what's working and what's not, especially when manually adjusting bids for various segments.

Example: If an advertiser introduces new keywords or pauses underperforming keywords, it can be difficult to adjust bids for the remaining active keywords without re-optimizing the entire campaign, which is labor-intensive.

9. Limited Insight into Overall Campaign Performance
Drawback: Manual monitoring typically requires the advertiser to manually review data for each individual campaign and ad group. This approach can prevent marketers from gaining a holistic view of how their campaigns are performing as a whole. It's easy to miss cross-campaign trends, such as which keywords are performing well across multiple campaigns, or identify overarching patterns that could inform better bid strategies.

Example: A marketer might not notice that certain high-performing keywords are consistently delivering better ROI across several campaigns. This information could inform broader bid strategy adjustments, but manual monitoring doesn't always provide this insight quickly enough.

10. Difficulty in A/B Testing and Experimentation
Drawback: Testing different bid strategies, creatives, or keywords becomes much harder with manual bidding. The time and effort required to set up, monitor, and adjust bids for each test can hinder experimentation and slow down the ability to identify the most effective strategies.

Example: Testing a variety of bid strategies or new keywords could take weeks when done manually, preventing marketers from quickly identifying and scaling the best-performing variations.

11. Increased Costs and Over-Bidding
Drawback: Without automated optimization, manual bidding can result in over-bidding on keywords or campaigns that are underperforming. Advertisers might fail to reduce bids on poor-performing keywords or keep increasing bids on terms that have already reached their maximum potential, leading to wasted budget.

Example: An advertiser may manually increase bids on a keyword that initially performed well, but over time, the keyword's performance may have declined. Without a timely adjustment, the advertiser could waste money on bids that don't convert at a profitable rate.

Conclusion
The drawbacks of manually monitoring and adjusting bids across multiple ad groups or campaigns include significant time investment, limited scalability, human error, delayed responses, and inconsistent bid strategies. As campaigns grow in complexity, manual bidding becomes increasingly inefficient, especially when trying to react quickly to market changes or optimize at scale.

For marketers handling large campaigns, adopting automated bidding solutions that leverage machine learning and real-time data can significantly reduce these challenges, improve efficiency, and lead to better bid optimization and overall campaign performance.