Managing your health requires achieving a balance between diet and exercise. In the same way, a healthy paid search campaign requires achieving a balance between branded and non-branded spending. Working together, the two create an optimal mix that will help you achieve the best results possible.

Why balance matters

Given branded terms’ reputation for delivering ROI, they often receive the lion’s share of a paid search budget. However, in this economy—where consumers are still hesitant to purchase—many marketers are not seeing the revenue from their branded terms that they had hoped for. As a result, they are desperate to find other means to boost revenues.

Fortunately, targeting non-branded terms can help you do exactly that. In fact, doing so not only has the potential to drive revenue, it can also increase brand awareness and spur growth—3 great reasons to invest in non-branded terms. Let’s take a closer look at each:

Growth. A paid search campaign that only spends on branded keywords will only grow as much as the brand recognition allows. By only investing in your brand, you leave growth opportunity to your competitors who are willing to make the non-branded investment. True growth, beyond the brand, comes from non-branded investment. If you are only investing in branded spend, year over year growth will be a reflection of your brand and the investments you’ve made towards it alone. In order to see year over year growth in paid search, you need to invest in non-branded spending.

Branding. If you want to increase brand awareness, you need to run paid search advertisements on relevant non-branded terms. After all, the search funnel begins with research, often with non-branded searches. Given that, it is important to get your brand in front of searchers when they are beginning their research. Ad copy that reflects your brand name may be one of the first touch points you have with that new user. Employing tracking that attributes the sale appropriately across each marketing touch point with that user will qualify your investment in non-branded terms that results in branded conversions.

Revenue. If your goal is to increase revenue from the dollars you invest, non-branded investment is an opportunity that has proven profitable for marketers. With accurate attribution management/reporting, non-branded spending can reflect its own profitability and that of your other marketing initiatives. Such attribution will be key to helping you find the optimal balance between branded and non-branded terms, and allow you to see how they are balancing each other in regard to ROI. In addition, this style of asset management may also teach you a thing or two about your consumers. In essence, it will allow you to leverage the data from your non-branded investment to improve your overall marketing and increase your bottom line.

Keys to achieving balance

But before you can configure your optimal balance between branded and non-branded terms, you first need to establish your minimum threshold of return. For example, if you could make $2 for every $1 you invested would you do it? Could you afford to make such a low return? Or, can you afford not to? Would it be better for your competitor to be spending that dollar and making two? Compared to the return you get from your branded spend, a 2:1 return doesn’t look that great. However when you are looking for maximized returns and growth, it spells possibility. Once you know your minimum threshold, you’ll be ready to push your investment to get the maximum return possible with the branded/non-branded mix.

While it can be tempting to solely focus on branded terms, smart marketers will incorporate non-branded terms into the paid search marketing mix in an effort to achieve the optimal balance that will deliver the most profitable return.

In case you didn’t see it there was an article in the Wall Street Journal this morning that seeks to capture a kind of shift or broadening of advertisers’ attitudes toward search marketing. Formerly search was something of an island and not well integrated into wider marketing campaigns. Many search + display studies and several years later it appears that marketers have developed a somewhat more nuanced view of search in the context of broader consumer behavior.

Here are some bits from the article:

Sprint is buying the top ads tied to phrases consumers tend to search for when they are close to making a purchase, such as “cellphone rate plans” and specific products like “Samsung Reclaim,” rather than more generic phrases they search for at the beginning of the shopping process, like “Sprint,” “AT&T” and “cellphone”  . . .

Volkswagen is coordinating its search marketing strategy with its network of 600 dealers across the country so it doesn’t end up competing against itself for the same terms and driving up prices…

[N]ew research from the search division of GroupM Search (a media buying and planning unit owned by ad holding company WPP) and online measurement firm comScore [ ] shows that consumers exposed to social media campaigns are likelier to search and click on that brand’s paid search ad.

“A few years ago, search was a little bit more progressive. Now, it’s mainstream,” says Simon McPhillips, director of media at Sprint. “The incumbents are trying to figure out, ‘What is the next new frontier?’

None of this is a surprise, nor do the examples above represent incredible sophistication on the part of marketers. It does however represent a widening of the “aperture” around search and search user behavior. As much as it may be driven by economics and not wanting to compete on brand or “generic” terms, which still constitute the majority of search queries, it reflects a better understanding that search queries occur in a larger context — of social media, display, traditional media and word-of-mouth-like viral behavior.

The article also speculates about how such trends are causing some slowing of search-ad spending at Google and how Google is pushing into other areas (display, video) as higher growth opportunities, as a consequence.

Can you apply the spirit of social media to other marketing channels?

At this year’s SMX East, after my presentation on Landing Page Usefulness—emphasizing a “usefulness” mission over “usability” tactics—it struck me: great landing pages can bring many of the ideals of social media to paid search marketing campaigns.

Here are five principles of social media marketing that can energize your landing page program:

1. Engage in specific conversations, not generic one-size-fits-all talk.

When a company engages in social media, the worst thing it can do is echo canned, cut-and-paste responses to every incoming comment. It’s painful just to imagine! Yet many paid search marketing campaigns commit that very faux pas: a user clicks on a keyword/ad combination with a specific promise, and then they are unceremoniously tossed to a general-purpose page. Such “message mismatch” between keywords/ads and their associated landing pages damages brands and hobbles conversion rates.

The reason I advocate deploying dozens—or even hundreds—of landing pages is because doing so lets you deliver focused and well-matched introductory dialogues with respondents, framed in their terms. As I said in my presentation, the goal is have respondents exclaim, “thank you, that was exactly what I was looking for!”

It’s not about optimizing one page to rule them all—an illusory, marketer-centric fantasy—but deploying many separate pages that each speak authentically to their niche. That’s the kind of respect that honest social media marketing shows to people reaching out to you, and a good landing page strategy can live up to the spirit of that goal.

2. Embrace “constant content,” continually releasing new ideas out into the world.

From blogging to tweeting, the engine of social media is the frequent generation of content. Hopefully it doesn’t take a committee or half a dozen pairs of hands to put up a new blog post or to update your Facebook fan page. The incentives in social media are to be fast, prolific, experimental, relevant and real.

The same tenets should apply to landing pages.

Sometimes, when I suggest that people should publish dozens or hundreds of landing pages, I get a look of incredulity: how could we ever create so many landing pages? Yet organizations who embrace social media marketing produce 10-times as much content without breaking a sweat. The resistance to such agile production of landing pages is often a hang-up from the bygone days of long-cycle web development. Today, deploying new landing pages should be as easy as—maybe even easier than—posting to your blog.

If you have a good content management system (CMS), a nice collection of page design templates, a shared library of images, maybe a few reusable Flash components, and a standardized mechanism for data collection and analytics tracking, then you’re ready to crank out landing pages on demand. And if you don’t have all of those pieces yet, none of them are particularly difficult to put in place.

3. Harness fast feedback to learn about your audience.

Arguably the best feature of social media is that it lets you tap into candid and immediate feedback from your market, albeit in an unstructured manner. It’s a wonderful environment to put ideas out into the community and quickly gauge reaction.

However, you can also solicit a different kind of feedback—more quantifiable and more directly connected to sales—through rapid experimentation with landing pages and keyword buys. Participation is more predictable with such PPC experiments, and the results can be easily benchmarked against your e-commerce or lead funnel metrics. It’s a small, low-risk investment that can help you discover big wins.

Struck with a novel theory about an unaddressed customer segment over your morning coffee? Don’t just hypothesize about it or file it for the next quarterly planning meeting. Launch a targeted search ad and tightly matched landing page for it before lunch and have real-world feedback by the next day. It doesn’t have to be perfect. You can test and tweak as you go along—an ongoing feedback loop.

Ads and landing pages also lend themselves to A/B tests, in a more controlled fashion than variations in social media tactics. If you structure your tests with good hypotheses, you can learn a lot about audience preferences and personas.

4. Open up a dialogue by asking relevant questions—and respecting the answers.

Social media is a conversation, not a soliloquy. People can ask questions, usually quite informally, to help identify the content or information that’s most relevant to their interests. This allows a single discussion to adapt itself to many different participants.

A similar dynamic can be achieved with landing pages. Sometimes, you have to field clicks from keywords/ads that appeal to several different segments of respondents. Instead of reducing the specificity of your content to a bland common denominator—the ill-fated, one-page-to-rule-them-all approach—start by offering them a few meaningful choices. Are you more interested in A, B, or C? Based on their one-click selection, you then deliver more detailed content that’s tailored to their needs.

This technique is known as multi-step landing pages or conversion paths. It can be a tremendous source of feedback, especially when you test different types of choices. However, it’s crucial that the choices genuinely help respondents find what is most useful to them—you want segmentation that benefits users, not just marketers. Remember, we’re striving for that “thank you, that was exactly what I was looking for” effect.

5. Champion transparency and authenticity over cleverness and technology.

The essence of social media is its authenticity, plain and simple. You can try to manipulate it with gimmicks and complicated machinery, but such machinations tend to fall flat. People love what’s real in social media, not what’s artificially crafted to appear real. Human trust is more important than plastic perfection.

Certainly this holds true with landing pages as well. There’s no shortage of sophisticated software you can use to dynamically alter your pages to users based on their IP address or behavioral profile. You can layer rules upon rules to calculate the optimal offer for each respondent. But inevitably, such overly processed experiences lose their authenticity.

Similarly, you can play UI tricks to try to force people to engage with your page (e.g., you must fill out this form before continuing!), but it’s almost always more of a turn-off than a successful hard-sell tactic. If you’re going to remove your regular navigation choices from a landing page, do so because it helps eliminate clutter for a respondent in that context—but still always give them an option to easily jump to your main site.

Be genuine, creative, open, and enthusiastic in your landing pages, and you will win more converts.

Landing pages, like social media, are something that you get better at by doing. So release your inhibitions and make more landing pages.

It’s time for an online advertisers bill of rights. So says Harvard assistant professor Ben Edelman, who has spent years researching Internet advertising and compares the current landscape to a “wild west.” Edelman recognizes the “staggering” opportunity that online advertising provides, but says the current system has problems that “threaten to destabilize online advertising—wasting advertisers’ budgets, slowing transition to online formats, and reducing payments to online publishers.”

In his just-published proposal, Edelman outlines five-point bill of rights for anyone advertising online:

1. An advertiser’s right to know where its ads are shown.
2. An advertiser’s right to meaningful, itemized billing.
3. An advertiser’s right to use its data as it sees fit.
4. An advertiser’s right to enjoy the fruits of its advertising campaigns.
5. An advertiser’s right to resolve disputes fairly and transparently.

Edelman uses Google’s advertising services and policies as examples throughout his proposal, sharing specific examples of practices that he says are harmful to advertisers. He says many of the “starkest problems” can be traced to Google’s online ad system:

“Google does not tell advertisers where their ads will be shown, omits itemized billing, limits how advertisers can use and transfer their own data, and insists on convoluted dispute resolution. Why such one-sided terms from Google?”

Edelman says he hopes his report leads to “improvements in at least the norms and expectations, if not the regulation, of online advertising.”

In an earlier post on Search Engine Land called Giving Credit to Keywords Where Credit is due, I mentioned we’d be following up on this topic with some future analysis. The analysis we’ve done is in the form of a case study, below.

Most companies have difficulty justifying the purchase of general top-of-the-funnel keywords such as “slippers” because typically, these types of terms don’t seem to convert-at least when measured using the last click method.  Add this to the fact that general terms are usually more expensive than branded terms like “LL Bean” or “Victoria’s Secret” and you’ll see why some marketers avoid them altogether.

So when marketers look at these kinds of non-branded keywords in their standard analytics package, they can see that they get a lot of clicks and that they’re spending a lot of money.  But what they cannot measure is the value that these ads bring.  In most analytics programs, these keywords actually look like they’re having a negative impact on sales and driving the cost per conversion up.

General keywords show negative profit

Prior to working with us, our client simply couldn’t justify the expense of these types of terms.  The analytics package they were using employed the last click method of attribution, which only gives credit to the last ad clicked prior to conversion.  By using the last click method, their analytics showed that only branded keywords, specific product names, and model numbers were having a positive impact on the bottom line and that general keywords were showing a negative profit.

The first step was to have the client move from a last click attribution model to one that gives credit to all of the ads involved in the purchase path.  The purchase path is the chronological sequencing of all ad clicks, banner impressions, organic visits and direct visits that lead to conversion.  Once they moved to this model, the customer segmented their top 50 keywords into five different groups:

• Competitive terms
• Product names
• Brand terms
• Model numbers
• General terms

Suggesting custom attribution settings

After they grouped the ads based on the above categories, we showed them a report that attributes even credit to each ad in the purchase path and shows even attribution with exclusions.  Exclusions are when you exclude giving credit to certain ads even though they appear in the purchase path.  In our client’s case, they excluded giving credit to any of their brand terms that occurred at the end of the purchase path as these types of keywords are almost always used for navigation and have no impact on the sales process.

By doing this, they were able to see how profit levels for the general terms quickly moved from a negative to a positive return.   They were also able to identify the amount of additional profit they earned from general terms which they chose to reinvest to acquire more clicks and ultimately more profitable conversions.

In addition, we calculated the number of additional visitors and clicks they would be able to purchase with their newfound profit from general terms.  The report also outlined the average profit per order.

Armed with these reports, the client was convinced that, when valued correctly, the purchase of the general terms did yield a significant profit and they therefore invested more dollars into their general top-of-the-funnel terms.

Attribution model leads to increase in ad spend, visitors and profits

The results were impressive.  As a result of reallocation, the client was able to determine the real value that their general terms had. Where the client used to only invest in a few ad sources, they now advertise in many different sources, as their ability to measure an ad’s success wherever it occurs in the purchase path has been greatly increased.

They also enjoy competitive advantage by purchasing general terms that competitors simply find too expensive when evaluated under a last click model.

Most important, however, is the fact that by using attribution management, the company was able to increase their number of visitors by 222% and, most importantly, increase their net profit by 131% over the course of 24 months.

First to pounce on the SEC 8-K filing by Yahoo was PaidContent, which provides an extensive bulleted list of many of the deal terms not revealed last week during the frenzy of conference calls and articles that followed the official announcement of the Microsoft-Yahoo search deal. CNET also writes about selected aspects of the deal contained in the filing, specifically an “escape clause” (termination) for Yahoo (see below). And the AP has a short piece on how the deal terms require Microsoft to hire at least 400 Yahoo employees.

Here are some verbatim excerpts from the SEC filing:

Negotiation and Execution of the Definitive Agreements

Pursuant to the terms of the Letter Agreement, the parties will negotiate and execute the Definitive Agreements as soon as practicable but in any event by October 27, 2009 (the “Negotiation Period”). If the Definitive Agreements are not executed during the Negotiation Period, the parties will submit any disputes regarding the final terms of the Definitive Agreements to an arbitration panel.

Conditions to Commencement and Termination Prior to Commencement

Prior to the Commencement Date, the Letter Agreement and Definitive Agreements may be terminated only by (a) mutual consent, (b) if a breach renders a condition incapable of being satisfied by the Termination Date (as defined below), or (c) if the conditions to commencement have not been satisfied by July 29, 2010 (the “Termination Date”); provided that Yahoo!, in its sole discretion, has the right to extend the Termination Date by six (6) months if the required antitrust approvals have not yet been obtained.

Search and Advertising Services and Sales Agreement

For a period of ten (10) years beginning on the Commencement Date (the “Term”), Microsoft will be Yahoo!’s exclusive technology provider for algorithmic and paid search services and Microsoft will provide contextual advertising to Yahoo! on a non-exclusive basis. Yahoo! will be the exclusive worldwide relationship sales force for Yahoo!’s and Microsoft’s premium search advertisers.

The services provided by Microsoft under the Search Agreement will be provided on all web sites, applications and other online digital properties owned or operated by or on behalf of (a) Yahoo!, Yahoo! subsidiaries and Yahoo! joint venture relationships, as well as on software applications developed or distributed by Yahoo! or Yahoo! subsidiaries that provide access to or enable algorithmic search services or paid search services (“Yahoo! Properties”) and (b) Yahoo! Syndication Partners (as defined below), as well as software applications developed or distributed by Yahoo!’s Syndication Partners that provide access to or enable algorithmic search services or paid search services from Yahoo! (“Syndication Properties”). “Syndication Partner” means a third party with whom Yahoo! has contracted to provide algorithmic search services or paid search services.

Subject to certain specified restrictions, Yahoo! will have full flexibility with respect to the user experience, content and look and feel on all of its web pages, and will also be entitled to use the paid search services and algorithmic search services for non-internet search queries with minimal restriction . . .

Microsoft’s mapping services and mobile search services. Yahoo! may implement each of the mapping services and the mobile search services on a non-exclusive or an exclusive basis. Yahoo! also has the option to work with Microsoft to implement the services on other platforms. If Yahoo! elects to receive services for other platforms, it must receive such services on an exclusive basis.

Revenue Share Payments and Other Payments

During the first five years of the Term, Yahoo! will be entitled to receive 88% of the net revenues generated from Microsoft’s services on Yahoo! Properties (the “Revenue Share Rate”). Yahoo! will also be entitled to receive its share (at the Revenue Share Rate) of the net revenues generated on Syndication Properties after the Syndication Partner’s share of net revenues is deducted. For new Syndication Properties during the Term, and for all Syndication Properties after the first five years of the Term, Yahoo! will receive its share (at the Revenue Share Rate) of the net revenues generated from Microsoft’s services on Syndication Properties after the Syndication Partner’s share of net revenues and certain Microsoft costs are deducted.

On the fifth anniversary of the Commencement Date, Microsoft will have the option to terminate Yahoo!’s sales exclusivity for premium search advertisers. If Microsoft exercises its option, the Revenue Share Rate will increase to 93% for the remainder of the Term, unless Yahoo! exercises its option to retain its sales exclusivity, in which case the Revenue Share Rate would be reduced to 83% for the remainder of the Term. If Microsoft does not exercise such option, the Revenue Share Rate will be 90% for the remainder of the Term.

Microsoft will also pay Yahoo! a payment of $50 million annually during the first three (3) years of the Search Agreement. Yahoo! may use these payments to partially cover transition and implementation costs not otherwise covered under the Search Agreement.

Termination Provisions

Yahoo! may terminate the Search Agreement if the trailing 12-month average of the RPS in the United States (the “U.S. RPS”) of Yahoo! and Microsoft’s combined queries falls below a specified percentage of Google Inc.’s (“Google”) estimated RPS measured on a comparable basis or if the combined Yahoo! and Microsoft query market share in the United States falls below a specified percentage; (d) on the fifth anniversary of the Search Agreement, and any time thereafter, Yahoo! has the right to terminate the Search Agreement if the trailing 12-month average of Yahoo!’s U.S. RPS is less than a specified percentage of Google’s estimated RPS; or (e) subject to exceptions, either party may terminate if a law, regulation or order would have a significant, adverse impact on a primary aspect of such party’s intended benefit of the Search Agreement.

Transition and Implementation Plan

Microsoft will hire not less than 400 Yahoo! employees (the “Transferred Employees”) and will offer the Transferred Employees market competitive compensation packages. In addition, Yahoo! and Microsoft will mutually agree on a retention plan to be paid for by Microsoft to assist in retaining the Transferred Employees and an additional 150 Yahoo! employees to be mutually agreed upon between Microsoft and Yahoo! to assist with providing the transition services.

The deal seems broader than the “web, image and video” search scope we heard before. Yahoo can terminate the deal if certain targets aren’t meet surrounding revenue per search, benchmarked to Google. At the five year mark the parties can change who runs “premium sales.” The rev share percentages change accordingly.

On a related note, there’s an opinion piece in the Wall Street Journal that argues these terms give Redmond a bigger win than Yahoo in Microsoft CEO Steve Ballmer’s “win-win” scenario but that, in the larger scheme of things, Google may have already won the game:

The deal is a clear win for Microsoft and a qualified win for Yahoo. The big question is whether it makes any difference in the only contest that really matters, which is the one with Google. The risk for both Microsoft and Yahoo is that the contest is already over. Second place won’t really matter, especially as the competition shifts to Microsoft’s home turf: operating systems.

Related coverage:

• It’s Finally Official, Microsoft & Yahoo Make A Deal, Yahoo Gives Up On Search
• Live Blogging The MSFT – YHOO Search Press Conference
• Microsoft-Yahoo Deals 2008 & 2009, Side-By-Side
• A Search Eulogy For Yahoo
• Micro-Hoo Details: Q&A With Mehdi & Schneider
• The Microsoft-Yahoo Search Deal, In Simple Terms

Your ads are often not selling the products that you designed them to sell. We have found that upwards of 48.38% percent of the time people end up buying a product different than the the one featured on ad they clicked on, and upwards of 11.28% of the time they bought a similar product, but not exactly the same product as the ad they clicked on.

When conducting this analysis, we excluded keywords that were brand terms and general category terms. For example, if we were analyzing a site that sold camping supplies and someone did a search for “camping supplies,” we did not include that type of keyword in this analysis because any product that was sold from the site was a camping supply. Instead, we focused on keywords that were product names, derivatives of product names or about a specific type of product.

For each keyword and product combination we looked at, we placed them in to one of three buckets: Exact, similar and unrelated. “Exact” would mean they purchased exactly the same product or product category of the ad they clicked on. “Similar” would be if they looked for XYZ sleeping bag, but purchased ABC sleeping bag, meaning they still purchased a sleeping bag, but it was a different brand or model from their search. “Unrelated” represented when the users search had no relation to what they ultimately purchased.

After conducting this analysis, we found the following information:

The benefits of this analysis are many, especially when it is available as part of your advertising analytics solution. First and foremost is the accuracy that comes with understanding which products are sold by each ad. This insight allows companies to apply real margins to each conversion vs. an average margin. This accuracy ensures that clients never overvalue or undervalue the contribution an ad delivers. Given that bid prices are set and budgets are allocated based on the metrics we see in our advertising, it is imperative that these decisions are made on accurate data to ensure we are getting the most out of our ad budgets.

In addition to the accuracy of performance metrics, this analysis can also be used to improve the performance of ads by identifying business actions that can be taken. For example, one of our clients had a set of keywords designed to sell product A, and we found that 90% of the time they sold something other than product A. This discovery was brought to our client”s attention. Our client did an analysis of their own business to see if they could understand why people looking for product A chose to buy a different product. They looked at the price of product A relative to the price the competition was selling it for. They also looked at their selection, shipping, return policy, etc., on that product relative to their competition and determined they had the most expensive price for that category of products relative to their competition, and that some of their competiton offered a much better return policy. Based on these findings, they brought their pricing in line with the competition and changed their return policy. Now, that keyword sells what it is intended to sell 40% of the time versus the 10% rate before they had this information.

A lot of times we blame our advertising for the lack of conversions or lack of profit it produces. An ad”s job is solely to bring the right prospective customers to your site. It is your site”s job to then convert those prospective customers. This analysis shows how a group of prospects that are looking for certain products may never end up buying them. This also forces the advertiser to ask the question “Why?” The “why” very often has to do with your price, selection, tax and shipping, site navigation, checkout, inventory, and perceived credibility. If you always blame your ads without looking at these other factors, you will waste a lot of money and time manipulating your ads only to end up with the same results.

A deeper dive into this type of analysis can help marketers identify potential up-sell and cross-sell opportunities. For example, if you discover that a lot of people who search for peanut butter and buy peanut butter also buy jelly, you could target any customer going forward that has purchased peanut butter or jelly with an offer to buy the other product. You may also rearrange your site so products that are often bought in tandem are shown together to increase the up-sell opportunities. Another tactic marketers can use is to send custom email messages to their customers that offer them products that are either related to what they actually purchased or are for the product they originally looked for, but chose not to buy.

This information may come as a surprise to many marketers. “How can someone that is searching for one product end up buying something very different?” The reason why people do this is interesting, but not as important as knowing that it does happen. If you have the ability to see which products are actually sold as a result of an ad, then you have a major opportunity to improve not only the performance of your ads, but the performance of your overall business.

In a recent Search Engine Land opinion piece entitled Automated Keyword Bidding? More Like Automated Money Sink, the author espouses the view that automated keyword bidding is flawed because it is impossible for agencies to scale their systems to deliver positive results to clients.

While I agree with most of the points the author has raised, I believe his conclusion is wrong. Blaming automation for poor bid management is the equivalent of blaming a Ferrari for a car crash if a monkey was driving it.

The real debate is really optimization vs. automation. Many people confuse the two and perhaps it needs clarification. Rules-based bidding is sub-optimal and not a scalable solution for clients.

Rules in computer science are known as “heuristics” and are defined as rules of thumb that do not guarantee the best solution. However, a bid optimization algorithm does guarantee the best solution subject to the constraints applied – i.e. a spending target or a CPA/ROI goal.

There is also the issue that keyword performance based on 7 day or 30 day increments can lead to poor campaign management decisions. I agree with the author on this point. The flaw is that the marketplace is very complex and doesn’t account for factors such as news, seasonality or events making it impossible for a human to correctly figure out what bid would result in specific CPCs , ROI and position.

Simple curve fitting (i.e. what a smart high school student would do) will simply not work. Bid performance profiles for keywords can be vastly different. Keyword models themselves need to be sophisticated and require knowledge of techniques such as time series forecasting. Crunching this large amount of data needs a huge database and computational firepower. An excel spreadsheet will not do. However, the flaw here is not of automation but that of building poor keyword models.

Instead of avoiding firms that espouse “proprietary technology”, it’s better to ask the right questions to make sure they truly understand optimization. Some important questions to ask include:

1. Is your proprietary technology a rules-based or a portfolio approach? A lot of agencies say they do portfolio-based bid management, but what they really do is simply cluster keywords. That is not a portfolio approach. Quiz them about the portfolio approach and ask them to explain their method.
2. Is the technology you’re being sold a campaign automation tool or a bid optimization platform? The difference is huge. A campaign automation tool might have all the bells and whistles to speed up labor intensive tasks. However, it will not have the technology to help you maximize your performance. A bid optimization platform will maximize your performance and provide you with tools to speed up your day-to-day tasks. To take the car analogy further: an automation part is like the body of the car while the optimization is the engine. A sleek car body is nice to look at, but when you are performance driven, what you really need is a powerful engine.
3. What is the accuracy of your keyword models? If they are doing model-based portfolio optimization, they should be able to give you a simulation of revenue/CPA at every spend level. At Efficient Frontier, we do this for all our clients and have the capability to automatically generate these in real-time. Once you managed with the portfolio approach, you should find the simulations to be within +-10% accuracy.
4. What do you do for sparse data keywords? If data is sparse, you cannot use a simple rules based approach. Make sure you ask them their approach to solve this issue.

It is not automation that should be blamed for poor campaign management. It’s the improper usage of modeling and tools that leads to sub-optimal results. So remember, don’t blame the Ferrari for the monkey crashing the car. Ask the right questions of the owner of the monkey.

We exhibited at the Internet Retailer show in Boston recently. The signage in our booth touted that we had the ability to do attribution management. For that reason, a lot of people came up to us and told us about a situation they are facing that is very common with paid search marketers: their branded keywords were the only ones were converting and their remaining keywords were just driving traffic.

For each person that told me this, I asked them, ‘How do you measure the success of a keyword?’ They would say if it was the last ad clicked and converted, and had a positive ROI, then it was a good keyword.  I then asked them, “If you were a basketball coach, what stats would you look at during halftime to decide who is going to play in the second half?” The answer I kept hearing were points scored, assists and rebounds.

I then asked them, “Why for your basketball team are you counting assists as a success metric, but when you evaluate your online advertising, you only value points scored?” The answer that I received across the board is that, “I don’t have the ability to see the assists, I can only see the points scored, so that’s what I have to focus on.”

And this is the problem that online marketers continue to be forced to deal with.

By utilizing a technology that allows marketers to see the team of ads, or purchase path, that leads to a conversion, along with implementing a simple attribution model that attributes profit and revenue evenly across the ads in a purchase path, marketers can now value ads that assist. With this type of system in place, marketers will quickly see that they have been giving far too much credit to their branded terms, which typically fall in a closing position (last click), and completely ignoring the value of their top of the funnel keywords, which assist in the conversion path.

To take this model one step further, we recommend implementing a purchase path with exclusions model.  In this model, we exclude giving credit to brand terms that occur at the very end of the purchase path. Many studies have shown, and our own research has found, that when people type brand terms into the search engine, they are doing so to navigate back to the site they decided to purchase from.  Under a last click model, the brand terms in this scenario receive all of the credit, while the actual ads that did all of the selling early in the purchase path receive no credit. By using the branded exclusions model, the true credit is being given to the ads that did the work needed to receive a conversion.

The reality with paid search is general terms do work and have real value, as do other forms of ads that do a lot of assisting, like display, comparison shopping engines, email marketing, etc., but you need the ability to measure their performance across a purchase path.

If you’d like more detail and insight into this topic, we’ll be publishing some further analysis in the coming weeks.

At the Rimm-Kaufman Group, we’ve spent a good bit of time over the last year studying the impact of multi-channel marketing on PPC advertising. By studying all traffic to our client’s sites we can determine how often multi-channel interactions happen, how the different channels behave, how they’re involved in multi-touch interactions and tendencies to be first rather than last. Armed with this data, we can then see how different allocation schemes impact perceptions of each marketing program.

Previously, we tried to put the “PPC Buying Cycle“—touches on multiple PPC ads—into its proper perspective. Turns out it’s a pretty small effect. Unfortunately, many agencies continue to hype the effect as they seem solely interested in having their clients spend more rather than spend wisely. Is the same true with the “Cross-Channel Buying Cycle?” Yes and no.

As we look at the data across a number of multi-channel retailers we’ve found that marked differences in the way consumers use each channel mean that cross-channel interactions have profound impact on some channels and not much on others.

Likelihood of multiple touches

Channels that have the greatest likelihood of multiple touches have the most potential to be impacted by changing allocation from last touch to something more advanced. Our data suggests that the channels most likely to involve multiple touches are affiliates, comparison shopping engines and email.

Consumers who buy after clicking a competitive (non brand) paid search ad are the least likely to have been to the site previously through a different channel. In our research, only 10 to 20% of buyers who touched a PPC ad last came through any other channel previously. Compare this to affiliate traffic, where 60 – 75% of buyers came through another channel first.

This means shifting from last touch to shared credit to first touch allocation only impacts 10 to 20% of PPC orders, while the same shift has a much larger impact on the perceived value of affiliates, comparison shopping engines and email.

Initiators versus followers

If channels were all equally likely to be first as last in multichannel interactions we might find that the net effect of changing allocation schemes is zero. That turns out not to be the case. Some channels are far more likely than others to be the first touch when more than one channel is used.

Competitive PPC is much more likely to be the first touch when there are multiple touches involved. This means that moving credit from last touch towards earlier touches does tend to “help” PPC. Natural search benefits from this same phenomena.

In contrast affiliates are almost always the last touch in multi-touch interactions, meaning shifts away from last touch credit have a decidedly negative impact on the perceived value of affiliate programs. Comparison shopping engines and email tend to suffer as well.

The net effect

What we’ve found is that these two factors together mean that yes, in fact, the perception of PPC benefits from crediting earlier touches in the cycle. However, because fewer PPC orders are in play than other channels—that first effect—the change is smaller than many folks seem to think. Indeed, in our research moving credit from 100% to the last touch to 100% to the first touch, competitive PPC only picks up 5 to 10%. Less dramatic allocation shifts take those numbers down even further.

Shop.org is organizing a group to define standards for credit allocation. I’m going to throw my name in the hat to join said group, but I fear that some of the folks in the group may be more interested in trumpeting the effect than measuring it. We shall see.

In the meantime, I’ll post more of our findings over on RKGBlog.