Blog: Tag: Keywords
As a great soccer player’s wife once said, “So tell me what you want, what you really really want.” She wasn’t talking about paid search bid optimization but marketers should consider, do you want impressions, clicks, leads, sales, revenue, or profit? For some advertisers, any of those will do because their costs per impression, click, lead, sale, unit of revenue, and unit of profit are about the same regardless of their ad spend. That is, each dollar of advertising generates about the same number of impressions, clicks, leads, sales, revenue, and profit regardless of how many dollars they spend (when properly optimized with an application like OptiMine’s). For many advertisers though, this isn’t the case and they must pick what they really really want. Here’s a case in point from retail financial services. For this advertiser, keywords, and competitors, cost per lead is about $33 regardless of how much they spend. Each incremental $33 of spend gets another lead. However cost per sale is about $150 when spending $20,000 a day but $300 when spending $40,000 a day. To understand this, consider a real example from the credit card business a few years ago, before the credit crunch. Back then, if you bid on the paid search phrase “credit cards for people with bad credit,” then you would get a lot of applications (leads). However, you got few sales (new accounts) since the people who search on that phrase rarely had their application approved, thus driving up the cost per sale.
Keyword Bid Optimization] Paid-search bid optimization comes in two flavors: rules-based and model-based. Within the broad realm of model-based optimization, you’ll find three common methods: global cluster-level modeling, local keyword-level modeling and global keyword-level modeling. Each has pros and cons and each offers various degrees of performance improvement. If you’re not certain what method you’re using currently, or are considering changing what you’re doing, read on for an overview of these different optimization approaches and their relative strengths and weaknesses.
A few months ago OptiMine published its first white paper, "Achieving the Gold Standard in Paid Search Bid Optimization". In it, OptiMine CTO Rob Cooley made the case that using global keyword-level modeling to optimize keyword bidding is superior to other modeling techniques a that employ clusters. The reason, quite simply, is that keyword-level modeling treats each and every one individually, regardless of the number of keywords.
Achieving the Gold Standard in Paid-Search Bid Optimization" was the first white paper published by OptiMine and remains the most widely distributed. One of the reasons for its popularity is the way it distills the complex world of bid optimization methodologies into an easy-to-understand guide. Whether you are a paid-search veteran, or just starting out, the Gold Standard white paper will help you segment and understand the differences in approach and results among the various optimization techniques. Today we embark on a series of posts that excerpt Achieving the Gold Standard. We begin with an overview of paid search.
Today we continue excerpting "Achieving the Gold Standard in Paid-Search Bid Optimization". The last post provided an overview of paid search, setting the table for the discussion of rules-based and model-based methodologies. In addition to these two, we'll look within model-based optimization at the differences between local and global optimization. What may seem simple on the surface is really significant and dramatic in the financial impact it has on complex paid-search programs.