For this post, I want to go one step further and explain how you can use several different types of technologies for operational and project-based attribution. The tables below should help you select the most appropriate technology based on your own attribution needs.

Operational attribution allows an advertiser to see all the steps or clicks that led to conversion in real-time and continuously attributes conversion credit across the team of ads. The three most common technologies used for operational attribution are display ad servers, website analytics and advertising analytics.

Project based attribution focuses on your overall marketing program and produces an optimized marketing spend plan, and its solutions include both technology and service providers. For project-based attribution, there are two commonly used technologies: business intelligence and advertising analytics.

This famous opening line from A Tale of Two Cities accurately describes the life of two keywords that reside in two very different countries (paid search campaigns). These two keywords were identical twins separated at birth. One keyword moved to Country A, which followed the law of last click attribution. The other keyword moved to Country B, where they followed the law of attribution management.

“It was the spring of hope” for the keyword that moved to Country B; “It was the winter of despair” for the keyword that moved to Country A.

Let’s now examine why these two identical keywords live such very different lives. Each of these keywords are classified as general terms, such as “toys,” “furniture,” “office supplies,” “laptop” or “shoes.” Thousands of searches are done each day for each one of them, and very often, more refined searches, such as “outdoor toys,” “leather sofa,” “automatic stapler,” “MacBook Pro” or “black high heeled shoes,” will follow them. Like all general terms, they most often occur at the top of the conversion funnel, which we would classify as “introducers,” meaning they’re often the first step of a purchase path. We can also classify some terms “influencers”—the middle step(s) in the path, or as “closers”—the last step in the path or conversion funnel.

On the surface, each of these keywords has a very similar life, in terms of search volume, click cost, and where they appear in the purchase path. However, how they are valued by their countries is where they differ greatly. To highlight this, let’s look at some metrics for these keywords over the last 500 clicks:

Keyword	Last Click Profit	Profit per click	Attribution Profit	Profit per click
A	$100	$.20	N/A	N/A
B	$100	$.20	$250	$.50

As the chart shows, these keywords performed exactly the same. They each contributed 35 times in purchase paths (introducers + influencers + closers = total contributions by that keyword). When each keyword is valued solely on its ability to close, they too are exactly the same ($100 last click profit). However, in Country B, the land of attribution, they don’t just see value in a keyword’s ability to close, but also in the keyword’s ability to introduce and influence people to buy. Therefore, when Country B determines the value of a keyword, they also include the number of times it was an introducer and influencer into their value calculation. This is what is known as attribution management, the process of properly identifying and valuing the chain of marketing initiatives and advertisements that lead to a sale or conversion.

These countries both have the same goal established for every keyword in their country. In order for a keyword to be allowed to continue to live, it needs to achieve a $.20 profit per click. Based on the charts above, keyword A is currently generating $.20 of profit per click, and keyword B is generating $.50 of profit per click. Based on the established goal, each of these keywords should be allowed to continue to live today.

Each of these countries also calculates the maximum bid price they can afford (assuming its conversion rate remains constant) to pay per keyword while still achieving the $.20 profit per click. In keyword A’s case, they are currently at the maximum bid, which is $.10 per click, whereas keyword B could have a bid price of up to $.30 per click to still achieve the goal of $.20 profit per click (500 clicks x $.30 cost per click = $150 ad spend, producing $100 of profit. $100 profit divided by 500 clicks = the goal of $.20 profit per click).

These two countries share another similarity in that they apply more financial resources (ad budget) to keywords that are performing above the goal of $.20 profit per click. By applying more financial resources and increasing the max bid, they are able to get more clicks on that keyword, which in turn yields more profit for that country. Under this system, general terms in country B can often be among the top performing keywords in that country, but in country A, these general keywords may be stuck at a lower bid or even paused (killed).

As you can now clearly see, the lives of two identical keywords are incredibly different simply based on how their performance is valued. Keyword A is close to being killed, whereas keyword B is regarded as a hero, performing far better than expected. In the world of online marketing, if you are still using last-click laws to value your marketing, you have likely killed a lot of innocent keywords and rewarded other keywords that are not truly deserving of that honor.

In Country B, which has far more progressive laws for the valuing of keywords, they are able to identify the real value of a keyword by looking beyond just its ability to close. As a result country B can then move on to more sophisticated attribution models, like implementing law that excludes giving credit to branded terms that occur at the end of a purchase path, as they deem branded terms at the end of a path are only used for navigational purposes rather than contributing to a conversion.

In this tale of two keywords, Keyword B will experience “the best of times in the age of wisdom,” while Keyword A will live in “the worst of times in the age of foolishness.”

How to structure a proper attribution model

So, how can you make sure that your marketing campaigns experience “the best of times in the age of wisdom”? To start, here’s a low cost process that you can go through to see the impact of attribution:

1. Determine the average number of visits per conversion on your website. You can get this information from any web analytics tool, including Google Analytics, which is free. If the average number of visits per conversion is much greater than one, then you know your average customer is requiring more than one visit to your site to convert. If you’re using last click attribution, you are giving too much credit to the last click and no credit to the influencers and introducers that are also integral to the conversion.
2. Bucket your keywords into the following 3 categories: introducers, influencers and closers (do this for your paused keywords as well). This exercise is going to require some educated guesses, unless you have a technology that does this for you. An introducer would be the most general terms that describe your business, like “toys,” “shoes,” etc. Closers are brand terms, model numbers and exact product names. Anything that is not classified as an introducer or closer can be put in the influencer bucket.
3. Count the number of introducers, influencers and closers you currently have in your active campaigns. Are you heavily favoring your closers and ignoring many introducers and influencers?
4. Count the number of introducers, influencers and closers you currently have in your paused campaigns. Are you finding that the majority of these paused keywords fall under the introducer and influencer categories and very few are closers?
5. Run a report that shows the number of times these closing keywords have converted each month over the last year, in order to establish a baseline.
6. Of introducers and influencers that you have paused, select a large enough sample size that generates significant traffic and truly describes the business you are in, and turn them back on. For example, if you’re selling baby furniture and you have the keyword “baby furniture” paused, turn it back on.
7. You’re going to have to measure the impact that these introducers and influencers have. First, count the number of conversions they currently receive under last click (just because a keyword is typically an introducer or influencer doesn’t mean it will not act like a closer some times), and more importantly, ask whether the keywords defined as closers now have more conversions, especially your branded terms, compared to the baseline report you created in step 5?
8. While you’re studying the numbers above, you will likely recognize two things that could concern you:
   • Your overall conversion rate has decreased
   • Your cost per acquisition has increased.

   This is to be expected. Why? As you invest in introducers and influencers and only measure by last click, your introducers and influencers will appear to not contribute to conversion rate. Because you are buying more advertising, you may find that your overall CPA does rise, but that is not always the case.

9. Ask yourself this question: Is increasing conversion rate and lowering CPA the reason why you’re in business? No. The reason you’re in business is to generate profit. It may seem counterintuitive, but overall profit can increase even while conversion rate decreases and CPA increases. So, the real metric to look at is total revenue. How much of an increase in revenue did you receive by adding introducers and influencers back into your campaign versus not having them at all? If you see a healthy rise in revenue, then you can likely conclude that having introducers and influencers in your campaign has been successful.

Follow these steps and you’ll likely discover why more and more marketers are developing more sophisticated attribution models for their paid search campaigns, rather than simply crediting the last click in the conversion funnel.

I found it interesting this week to read What Celebrities Make For Twittvertising, which discussed the heavy payouts celebrities receive for tweeting about various products and brands. After reading this, I couldn’t help but think about how this relates to valuing a Facebook fan, so I decided to have some fun by identifying ways to truly value these celeb tweets.

The article provided us the price per tweet that some celebrities are receiving. We wanted to figure out how that translates into a CPM and a cost per follower (CPF). The chart below presents our findings:

Follower data as of 1/18/10

So, what are some takeaways from here?

A lot of these celebrity tweeters seem to reach similar audiences and have similar celebrity status, so it makes sense to choose the celebrity that has the lowest CPM. This really does come down to price and the right celebrity tweeter, whereas when buying display advertising, CPM and reach are important factors. One also has to consider where your display ads will appear, which is not something needed with tweetvertising.

If you believe a Kardashian would be a good tweet-model for your company or brand, then it makes the most sense to pay Kim’s fees because she has a much lower CPM and CPF compared to her sisters. In addition, Kim likely shares much of the same audience as her sisters, plus has additional followers.

Quite frankly, it’s a bit surprising that Kourtney can charge the fee she does. After all, as the table confirms, Kim’s the real star (2,824,011 followers for Kim vs. Kourtney’s 778,620).

Other questions that came to mind after reviewing this information:

Should there be a flat value for CPM? An audience of 1,000 followers, whether they’re following a celebrity or an unknown, is still 1,000 followers to an advertiser.

Could my tweets about products and companies be worth more to advertisers because they are less likely to be perceived as advertising since I am not famous? As it turns out, there are companies willing to pay me for my tweets. For example, Ad.ly will connect me with companies willing to pay me for my tweets and has set a price of $2 per tweet. That translates into a $.002 cost per follower, which makes me a bargain compared to these B-list celebrities.

Do celebrity spokespeople translate the same with Twitter as it does for traditional marketing? Or are celebrities on Twitter perceived as producing “manufactured” word of mouth? Do readers of tweets by celebrities draw a line between personal opinion and advertising?

I’d love to hear more thoughts and ideas of how others in the online marketing world would answer these questions, along with what other questions come to your mind. Are you currently getting paid to tweet, and if so, what is your CPF? Has anyone’s company ever paid for tweets or have you considered paying for celebrity tweets?

If you agree with these statements so far, you should also agree that any improvement we make to the accuracy of measuring our marketing effectiveness, the more profit we stand to garner.

Attribution management is about giving credit where credit is due, but herein lies the marketers dilemma, “How much credit is due?” Every marketer that has used or contemplated attribution has struggled with this question. Most marketers have struggled with this question so much that they’ve chosen to not implement an attribution strategy. Instead, they continue to use last click attribution.

If you’re still reading at this point, that means you have agreed that any step towards accuracy improves profit, but if you haven’t implemented an attribution strategy because you are unaware how much credit is due, you are essentially contradicting yourself.

Yes, attribution can be an incredibly complex mathematical exercise to develop a proper algorithm to accurately value all of your advertising. However, to be more accurate than the last click, it does not have to be complicated at all.

When we start working with a new client we have the ability to develop very complex mathematical models to more accurately assign credit to where credit is due. However, we cannot offer that on day one because we don’t have enough client data to build sound mathematical models. Does that mean that we keep a client on last click for months or maybe longer until we collect enough data to apply an accurate algorithm? Absolutely not.

The first thing we want to do is get them removed from the most inaccurate attribution model that exists today—the last click. The attribution model that we put in place on day one is an even attribution model, which takes the profit and revenue earned on a conversion and distributes the credit evenly across a team of ads that we tracked a specific lead to a conversion. We have found across our entire client base that this simple, yet more accurate attribution model, does increase their profitability, which is the ultimate evidence that we need to trust this “simple” attribution model.

We also, on day one, implement one more simple model that further increases the accuracy, which is to exclude giving credit to brand keywords when they are the last click of a purchase path. We have found, and other research indicates, when brand keywords are the last click in a path, that it is a navigational search, and when we give credit where credit is due, we want to give credit to the ads responsible for the sale, not an ad that was purely navigational.

When it comes to attribution, I like to quote one of our partners, Andrew Wheeler, Managing Director at iProspect Chicago: “Think evolution, not revolution.”

Evolution is implementing a model, like even attribution, whereas revolution is going from last click to algorithmic attribution. If you believe that increases in accuracy yield more profit, then you should believe that a simple switch from last click to even attribution will be more accurate and thus more profitable. This model has been successful for our clients, and I have no doubt that it will be successful for you too.

“The de facto industry standard of measuring the value of campaigns or media placements by the most recent click or interaction is ripe for change.”

The report continues by defining interactive attribution as “the practice of measuring the correct partial value of each interactive ad that drove a desired outcome.”

Reading the report will give you an understanding of how Forrester sees each vendor in the space and what each vendor’s strengths and weaknesses are. One key point in the analysis is there is not one specific way to do attribution—each vendor approaches attribution in a unique way. For this post, we’re going to focus on the two specific types of attribution: “operational” (or day-to-day) attribution and “project-based” (or strategic, high-level) attribution.

Operational attribution

Operational attribution allows an advertiser to see all of the steps or clicks that lead to conversion in real-time and continuously attributes conversion credit across the team of ads. The benefit of operational attribution is that all of your daily marketing decisions (bid price, CPM, ad text and ad sources) reflect accurate attribution, so each click gets the credit it deserves.

In order to perform operational attribution, you need the ability to track the performance of your advertising in real-time and must be able to track all forms of online advertising, not just one medium, to get an accurate picture of how much credit each type of media deserves.

Another requirement is the ability to track conversions that do not occur online. Many conversions from online advertising may occur via the phone, CRM or ERP, or in a point-of-sales system. The best attribution solutions, according to the Forrester Report, support both online and offline conversions, and also include “out of the box” attribution models that can be used on day one.

Project-based attribution

Project-based attribution focuses on your overall marketing program and produces an optimized marketing spend plan, and its solutions include both technology and service providers. Project-based attribution analyzes historic advertising, as well as factoring in new or changed information, to determine the best advertising mix for the future.

Typically, project based attribution is performed on a time interval that makes the most sense for your business (quarterly, yearly, etc.), where you’re looking at attribution performed over that interval and measuring its impact during that time. Then, based on the previous intervals performance, and predicted outside factors that will occur in the future, you make a decision about the best way to attribute your marketing dollars going forward.

To perform project-based attribution, complete and accurate historic ad performance data is required. This can create a challenge for project-based attribution providers since they must rely on their clients to provide the data. If the clients’ data is flawed or limited in scope, then the models that they build will be flawed as well.

Forrester did a nice job of highlighting the spectrum of the available options to perform attribution today. Given that attribution is a relatively new field, Forrester notes that new methods are continuously evolving.

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.

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.

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.

A recent report published by iProspect, Search Engine Marketing and Online Display Integration Study was featured in an article for MediaPost titled Study Confirms Display Ads, Paid Search Work in Concert. Robert Murray, iProspect’s CEO is quoted in the article, saying “Internet users are more likely to engage and/or eventually make a purchase from brands with which they are already familiar.” Display ads help breed familiarity. The article also reports findings that suggest that of the people that react to display ads,  31% of those people click on display ads, and 27% go to search engines to do a search related to the ad (brand, offer, product).

At ClearSaleing, we have been tracking the relationship between display and search for over 2 years. We assemble advertising into what we call a purchase path, which is the chronological sequencing of display impressions, ad clicks, organic visits and direct visits that lead to conversions and/or non-conversions or abandoned paths. When we analyze the purchase paths of our clients that use display and search advertising, and specifically look at the types of searches they do after being exposed to display, we learn something very interesting.

Based on our observations, the combination of display advertising and paid search can indeed reduce your cost per acquisition (CPA). Our analysis shows that the most common type of search by a user after being exposed to a display ad is a branded search. We have found that with some of our clients, upwards of 50% of the searches that occur after being exposed to a display ad are brand searches.  A brand search is a search for your company name, a misspelling of your company name, or a typo of your company name that leads a consumer to click on your sponsored listing (your PPC ad).  Brand ads are almost always the cheapest PPC ads that you can buy. Many companies have trademark restrictions on other companies bidding on their branded terms, and for those that don’t have trademark protection, they are still likely to pay a very low CPC when compared to their non-branded PPC ads.

For example, if you were in the auto insurance business and are not running display ads, the most common search for your products is likely “auto insurance,” which is a keyword with a per-click cost between $15 and $30+ historically. Our research shows purchase paths that are all search-based typically start with a general term, and often include a second search for a non-branded term, and then close with a branded term. They also go from a general term to a branded term and then convert. The CPA, when considering the entire purchase path in this case, typically runs in excess of $30 to $60+.

If this advertiser ran display ads in addition to search ads, the search the consumer most often does after seeing that display ad is for a brand term. When we measure just the cost of the advertising in these converting paths, the cost for a banner impression is just fractions of a penny, and the cost of a click on a branded term is typically no more than $.25. Therefore, the cost of these converting paths can be as low as $.25 versus a cost of $30 to $60 for the previously stated search-only converting Paths.

By adding display to your campaigns today, you will create new paths for your consumers to navigate, which are much cheaper than search-only paths, and this can allow for your CPA to decrease and searches for your cheaper brand terms to increase.

One question that often arises from lead gen marketers is, “How do I optimize ads when I have a long sales cycle?” This question comes from two types of companies:

1. Those with long sales cycles and few conversions over the course of a year, like an individual Realtor.

2. Those with long sales cycles and a higher volume of orders, like a large B2B company, such as SAP.

The challenge that affects the first group is that they don’t have enough conversions during the course of the year to have enough statistically sound data to judge ads solely on the basis of their ability to produce profit.

The challenge that the second group has is not as difficult as the first group. When launching new campaigns or ads, however, they still have to wait for weeks, months or longer for the sales cycle to be completed.  In the meantime, how should they determine if their new ads are having the desired impact or not when it is too soon to be able to tie conversions and profit back to the ads?

In the absence of having conversion data to make optimization decisions, the next best method which satisfies the two examples above is to develop a lead scoring system or lead scorecard. A lead scorecard is a method for assigning value to a lead to determine how qualified that lead is. It could be represented in terms of an actual score (10 being most qualified, 1 being least qualified) or it could be scored according to the stage of the sales process that the lead resides in (new, first call, completed demo, sent out proposal, closed won/lost).

An online ad is good if it produces a qualified lead. An online ad is bad if it produces an unqualified lead. A qualified lead is one that is from a company or person in your target market, and they have the means to afford the product/service you’re selling, they are looking to make a decision in an acceptable timeframe, and they are responsive to your sales team’s phone calls and correspondence.

With your lead scorecard in place, you can now begin to make optimization decisions based on the quality of a lead that is generated from your advertising versus simply looking at the cost per lead or waiting until enough sales have occurred to make a statistically sound decision. For example, a Realtor should determine that an ad is successful if the leads that came from it took their phone call, setup a face-to-face appointment to see houses, were approved for a loan, and were looking to buy in a reasonable timeframe.

When you are a lead gen marketer, each sale requires two things. First, a lead must be generated, and second, the sales person has to do an effective job of selling. If you find you are generating a ton of qualified leads, but are not converting enough to sales, you most likely have a sales problem and not an advertising problem. All lead gen marketers can ask is for their advertising to produce qualified opportunities. If we focus on CPL, we are ignoring quality and are solely focused on quantity. It is important to remember that leads do not pay the bills. Qualified leads, when combined with a skilled sales team do. Make sure you are generating qualified leads and have the right sales team in place, and you will be a successful lead gen marketer.