Regularly researching keyword opportunities and expanding your term list is critical to the success of a paid search program, but knowing when to delete keywords with low potential is also an important consideration in managing PPC accounts at scale. Why Delete Keywords at All? In addition to the engines having finite account size limits, keyword lists, especially in large, mature accounts, can grow to an unwieldy size as new keywords are added throughout the years. This can make it more difficult to quickly enact time-sensitive changes such as promotional copy additions and intraday bid adjustments. Thousands of additional keywords translate into hundreds of additional adgroups and internet and search engine API bandwidth limitations restrict how quickly requests can be transmitted and processed. This issue is compounded if keywords need to be duplicated in various parts of the account for testing or geotargeting purposes. Also, while you may not see much in direct costs associated with allowing keywords that aren’t generating many clicks to continue running in the account, these no click/low click-through rate keywords may be lowering your Account Quality Score and indirectly raising the costs per click of other keywords in the account. Perhaps worse than not pruning low impression/traffic keywords at all, paid search account managers may arbitrarily decide to delete keywords that have not had an impression or click within a time-period of X, where X is a nice round number like 30 days, 6 months, or a year. We hope our analysis below will help account managers make a more data-informed decision, minimizing the negative impact this task could have on long-term sales. Before We Begin…
- We assume keywords without impressions, clicks, and/or orders have been appropriately optimized (ex. for low/no impression keywords).
- The data analyzed in this post categorized a single keyword with separate matchtypes and campaign settings (ex. location, language, networks, device, etc.) as separate, individual data points.
- RKG, while balancing financial risk and rapid learning, tends to set fairly aggressive initial bids, so the windows between a keyword's early impressions and clicks may be biased a bit shorter compared to more recent data, but the early data is still a reasonable proxy for future performance patterns. We are using the earliest data here in order to incorporate sales and cost figures generated over the full lifetime of the keywords.
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