Moreover, your most valuable customers are the ones who make a purchase and keep coming back, compounding the challenge of measuring latent conversions and optimizing bids.

In general, as time passes, marketers often see more and more value attributed back to an initial PPC click, but revising bid calculations after the fact results in chasing a trend rather than predicting one.

How you track latency and follow-on conversions can have a big impact on your bidding decisions and revenue-on-ad-spend (ROAS) calculations. Imagine pausing all your bids, yet conversions continue to come in attributed to Paid Search – it may seem like free traffic, but it’s not.

As an example, analytics packages such as Omniture SiteCatalyst or Google Analytics use “Date of Conversion” attribution, meaning that an order is attributed to the day when that order occurred, as opposed to “Date of Click” attribution.

Conversely, with “Date of Click” attribution, as seen with the Google AdWords Conversion Counter, conversions and revenue will accumulate onto clicks from days or even weeks earlier. You want to be a responsive marketer, but you are working with incomplete data.

Consider the following sequence of events for a single visitor and how they will appear to the marketer:

This makes several challenges apparent:

• For many marketers, the first order is just the beginning of the story. You want to optimize bids, creative, and landing pages based on the expected lifetime value of a new customer.
• Waiting for follow on orders to be recorded over time means that bid optimization would be constantly, but slowly, revising bids upwards – however, in many cases when the keyword in question is no longer relevant to a seasonal or promotional campaign.
• It is unclear how much of your customer loyalty should be credited to paid search. This will be a hot topic with your merchandising and service teams, who have created a compelling customer experience which generates its own loyalty. However, the important marketing question is whether search visitors would have found your site on their own? If not, then the visit has incremental value.

Smart Handling For Latency

Below is some sample conversion latency data from an actual online retailer. The green line indicates first-time orders as a percent of their eventual (one-year) total, charted by the length of time after a paid click; 87% of first-time orders occur on the same day as the click. The blue line is subsequent orders as a percent of eventual total subsequent orders.

As you can see from the chart, while 95% of “first orders” occur within a week of the paid click, only 83% of subsequent orders occur during this time period. It’s this latency with follow on orders that trips up even the most diligent marketer.

Your optimization and bidding should take into account the latent revenues driven by a paid click, but also needs to be responsive to market conditions. Some advertisers deal with latency by ignoring recent performance data and using a longer look-back window to calculate bids, but this ultimately prevents you from being able to react quickly to market changes.

Alternatively, most advertisers simply increase the value attributed to a click when latent orders arrive days or weeks after the fact. While this may be accurate, it still results in a missed opportunity to fully incorporate purchase trends into bid decisions.

Instead of waiting for follow-on conversions to happen, marketers can estimate expected revenue from subsequent sales at the time of the first sale, ensuring maximum responsiveness to changes in conversion rates and buying patterns.

By using historical data to estimate the expected value of a consumer from their first conversion, you can make more timely bidding decisions at the time of the initial sale. The concept is simple – if you knew that a consumer typically places 2.2 orders on average following their initial purchase, wouldn’t you bid more for that initial purchase rather than waiting for the additional orders to arrive?

Analyzing historical conversion data gives you enough information about consumers to estimate the average lifetime value given particular characteristics. (In the example chart above, 50% of the revenue was from follow-on conversions.) The most accurate and responsive attribution and bidding systems should use this estimated lifetime value to calculate bids, making appropriate bid adjustments much closer to the date of click instead of the date of latent conversions.

In a world where seasonal and promotional cycles can be as short as weeks, speed can mean the difference between winning and losing for PPC marketers. Estimating lifetime value allows you to react more quickly to changes in user patterns to maximize total revenue.

Using this type of modeling, you can use a lifetime value estimate to make decisions based on conversion data closer to the date of the paid click. Being able to predict the impact of early consumer indicators and factor it into bidding decisions will allowing you to capitalize on trends before the competition does, increasing revenues and ultimately market share.

As reported here on SEL by Danny Sullivan, some early research showed gains for Bing, while other reports showed traffic patterns across all the search engines remaining largely the same. Those reports looked at visits to each engine and the number of searches performed. At Marin Software, where we closely track paid search spending, we did see a slight increase in spending in Microsoft Advertising – during a week when spending on both Google and Yahoo dropped slightly. And the spending jump was based on an increase in the number of clicks, not the cost per click. This probably makes sense, as Microsoft did not do a strong outreach effort to advertisers in advance of Bing’s launch. It’s still unclear how Bing will impact the SEM market in the long-term. In the meantime, here are three tips search marketers should keep top of mind when running paid search programs on Bing.

Keep Bing’s differences in mind

Many marketers have never bothered to move their Google ads to Microsoft Advertising, but you should. Just ask your Microsoft Ad rep if they will accept an export from your Google account, and you could be up and running quickly. It doesn’t have to be a lot of your time, but will result in incremental traffic to your site.

The conversion rate may be slightly lower on MSN.com for some categories, so you can keep the same bids or lower them by about 15%. For lead generation categories such as insurance, weight loss, or credit checks, the conversion rate actually appears to be better on MSN, perhaps due to differences in quality score enforcement and possibly demographic differences.

Think about the demographic differences carefully, as MSN/Bing users will tend to be less technology savvy. Of course, most searches are performed on Google for all users, but on the margin, Windows users who do not bother to change their defaults are more likely to end up at Bing, where as more technology savvy users will likely be using Firefox and Google. What is the impact of this for search marketers?  Depending on your category, your ads may be more or less suitable for Bing searchers.

Leverage Bing’s synopsis feature

The Bing “synopsis” feature (which shows a snippet from the results page) is beneficial to advertisers, as it will likely keep users on the results page longer, instead of clicking away to another site. Depending on the number of ads that show up, the mouseover can overlap the ads themselves (see below). In this example, the ad in position 8 (Kohl’s) gets better treatment than ads 5, 6 and 7.  However, for most advertisers, click-through volumes will be too low to draw any statistically significant conclusions from these differences.

Know the ins-and-outs of Microsoft Advertising

While Microsoft has launched a new look and feel for Web visitors with Bing, the backend and ad center are largely the same. While there are important differences between Microsoft and Google, the most critical issues are in measurement. When using Microsoft tracking, search marketers cannot track revenue amounts, only the occurrence of a sale. Assuming your orders are of different values, you will want to use another tracking technique such as Google Analytics, Omniture Site Catalyst, or Marin’s tracker. Don’t try to measure costs and conversions by different match types – it’s really not possible with Microsoft Advertising. There is, however, a nice parametrization feature that can cut down on the number of ad groups you will need, which is very handy for advertisers with a large numbers of products.

Bing is a blend of the old and the new, and best-practices in search marketing still apply. If you are managing very large search marketing programs, Bing probably won’t be the main focus of your job, but it was and is still a great place to pick up some incremental traffic. Here at Marin, and I imagine across the search marketing industry, we will pay attention to any demographic differences that the Bing front-end yields over time. But as with anything in paid search, you don’t have to take anybody else’s word for it – you can jump in directly to measure your own results.

While this is not a difficult concept to grasp, marketers today struggle to break down the problem into actionable tactics that can be readily applied to their PPC campaign. Which specific metrics should be attributed and how? What tools are currently available to marketers to achieve this? And which metrics can be measured with enough precision to increase real program profitability?

The right metrics

The customer lifecycle metrics most readily actionable to a paid search campaign are:

1) The value of a new-customer conversion. For companies where repeat purchases are relevant, this is the expected value of both the up-front purchase and any subsequent revenue events. Also known as life-time value (LTV). 2) The percentage of campaign-converted customers that are new vs. returning.

Both of these metrics are powerful tools for more accurately valuing paid search conversions by taking into account the customer lifecycle (either measured or forecasted) that surrounds it. While overlapping in some areas conceptually, the mechanisms to track these metrics and the ways in which the data sets need to be applied are quite different.

With the first metric, the marketer seeks to find areas within his or her PPC campaign that produce a high degree of retained business after the up-front purchase (or click). Take a site selling baby clothing. As a group, users who converted on the term “newborn clothing” may have more LTV potential than those acquired on “toddler shoes.” The key is to measure the combined lifetime value of all conversions for as many individual adgroups and keywords within the campaign as possible. Once enough data has been collected, these values should be attributed back to the upfront click when calculating ROI, and factored into the bid rates being set. Clearly, running manual LTV analyses for the myriad components of a PPC campaign would require significant effort. Happily, search marketing application providers have developed robust capabilities in this area, enabling marketers to achieve these analyses quickly and efficiently.

With the second metric, marketers apply retention data to determine how much of the transaction “credit” to award various areas of the campaign for the conversions they generate. Keywords and ad groups converting a higher percentage of repeat users might be awarded a discounted portion of the additional revenue because some of those sales would likely occur anyway. This discounting is particularly relevant when assigning monetary value to actions that induce future sales (read more about this in our previous article, Attribution Alchemy: Mining Your Sales Funnel). If a sales-inducing action is completed by a new user, that action is more likely to directly affect future behavior and that click (in the case of paid search) is more valuable. In contrast, for the case of a repeat user, the user’s prior experience is a powerful factor. Furthermore, because the first purchase was being overcredited, the subsequent purchases need to be undercredited to make the total come out to be zero (whereby your allocated value will match your actual value).

Again, once the expected full lifetime value (metric #1 above) has been factored into ROI measurement and bidding, attribution should be adjusted based on whether a transaction is completed by a new or repeat customer. As you can see, this is where the two metrics discussed in this article overlap directly. Conversions by new users are much more likely to deserve full attribution for the multiple conversions expected to occur during the customer lifetime. Conversions by repeat users, however, are typically awarded less credit, because a higher portion of future sales would likely occur anyway.

Timing is everything

A major point of distinction between these metrics is the time period over which data must be measured.With the first metric, retention sales of users driven through the PPC campaign must be analyzed over weeks and months to get the necessary data. The need to conduct this analysis at the unique user (vs. visit) level also requires tools with powerful backend processing. In the second, the feedback is more instantaneous, as shopping carts and analytics packages will know upon close of the up-front sale or conversion, whether the customer was new or repeat. While tools exist to measure this and automatically adjust bid rates accordingly, marketers can get started today with top level analysis of the percentages of new/repeat customers driven by their major ad groups. Once completed, this can be used to make educated decisions as to which ad groups deserve more or less credit for the conversions they produce.

Clearly, factoring the full customer lifecycle, including past and future activity when determining how much to pay for a conversion today, can greatly improve campaign scale and efficiency. Luckily, the tools needed to measure, forecast and attribute pre- and post-click activity into ongoing management are increasingly available to marketers these days.

As a professional search marketer, how can you breeze through this instability and embrace it to drive maximum effectiveness from your campaigns, while keeping ROI steady? Believe it or not, it’s possible to craft an effective SEM program during volatile times, if you follow a few simple strategies. The following SEM tips and techniques will eliminate wild fluctuations in your campaign effectiveness and help you get the most out of your pre-determined SEM budget. Be clear about your goals. Search is very measurable but you need to know what to measure first. Are you selling a product? Trying to generate leads or registrations?  Does the conversion event take place on your website, on somebody else’s website, over the phone or in a store? Once you have made a list of your unique situation and specific goals, you can start to put some clear measurement practices in place.

Measure your Results. The goal for most search marketers is to maximize spend on the campaigns with the highest ROI, but first you need to identify those campaigns. To find them, measure campaign results using the metrics of success that define your business, from online conversions and purchases, to completed lead forms. Measuring these results on your own site is easy, since all three major publishers (Google, Yahoo, MSN) have free tools to help with this. Conversions that happen on other sites, or offline, are also trackable, but require that you put apply ID numbers at the ad and keyword level, and then track which IDs converted on the back end.

Change your concept of a “budget.” For many businesses, results from paid search advertising can be measured almost immediately in the form of site visits that result in a purchase or lead. So it makes sense to set goals by investment-per-conversion, rather than setting an overall paid search advertising budget. If you know already what your ideal lead value is (for example, $20 per lead, or maybe $3 of revenue for every $1 of spending), then fine tune your search marketing program to get as many leads as you can at that value. Of course, you can set hard spending caps as well; you just may want to set them high enough so you won’t consistently max out before the end of the day.

Tune your site and your ads. The relevance of your landing pages and ad creative to each keyword is as important as your bid. Plus, optimizing your site and ad copy can help boost organic search rankings as well. Take the time to break up your site into dedicated landing pages for each of your major offerings or product lines. This will result in higher quality scores and, in turn, more traffic for the same amount of spending. When creating new ad copy, be sure to test it head-to-head with the existing copy at a 50/50 split to prove which performs better in terms of overall conversions or profitability. Once the top performing copy is identified, eliminate the losing version from rotation.

As search marketers, we can’t change the environment in which we create, launch, and manage our campaigns. But we can embrace the fluctuations and ride out the wave of market conditions by positioning ourselves for success to obtain the best results possible for our campaigns.

Wister Walcott is co-founder and vice president of  products for Marin Software, and is an experienced technology executive with proven sales and marketing expertise.