Programmatic Advertising is a up and coming buzzword for online marketeers. Originally it was used as a way to describe buying and selling blocks of display advertising, it has now changed and is increasingly gaining momentum in the marketing community. Programmatic advertising today is used to describe the process where clicks are purchased based on detailed knowledge about the specific click (keyword, match type, cost/revenue/profit history, mobile vs desktop, new visitor vs repeat visitor history, etc.). If done right, you know the cost of revenues or profit for the next click you are about to buy, before you buy it.
What does this have to do with Google Shopping?
I will use an example of a merchant with 5,000 products in their catalog. Each of these has different selling prices ($10 - $2,500) and a range of margins (3% - 70%). Would you pay the same for a click to a product that sells for $10 with a 3% margin as you would for a product you sell for $2,500 that has a 70% margin? Ok, it is an extreme example but it makes the point clearly.
Calibrating how much you pay for each click should match the price of the product, the margin of the product, the total amount the specific PLA brings to the shopping cart checkout, etc. That Max CPC then needs to be adjusted with bid modifiers (Mobile, repeat visitor/remarketing, etc).
The example I used above with a merchant having 5,000 products in their catalog wants two things from their campaign: (1) grow revenues as much and fast as possible, and (2) ensure that the cost is controlled very tightly for the growth. The amount of products and the number of variables that needs to be kept under control makes it impossible to do this manually.
The options the merchant has is to use an agency to manage this for them or use an internal team that has access to automation tools. Both these approaches requires a lot of coordination or a wide range of tasks; campaign structure, bid adjustments, product group exclusions, setting Max CPC for new products, updating Max CPC to reflect changes in performance and competitive metrics, updating to adjust for mobile performance, updating to adjust for visitor history (i.e. repeat visitor with abandoned cart history) conversion rate impact, and so on. A programmatic approach to the above keeps adjusting all these variables and keeps track of how each of these changes impacts the other variables.
In our upcoming webinar with Google Shopping next week we will cover in great detail how this approach can help your business and how it has helped others. We will offer case studies and show why Programmatic Advertising is such a big deal for advertisers.
Programmatic Advertising is a way to drive quality, accuracy and predictability for your account (think knowing the profit of the next PLA click before you buy it), it is not a matter of IF but WHEN you will utilize Programmatic Advertising for your business.
Bjorn Espenes, CEO of Finch, recently did a joint webinar with SEMRush explaining how expanding your keyword bank can enable growth revenue if done the right way. He talked about how many companies will experience growth stagnation in active keyword expansion of their AdWords account. Here are 2 major challenges he addressed in expanding your keyword bank.
Managing the growth of your keyword bank can be time consuming to research new keywords, add them to a campaign, and track performance. Trying to determine how much to bid on each new keyword will not only be time consuming as well, but will also increase the risk on money your company will spend on AdWords. At Finch, we have developed a tight way to handle this in an almost automated fashion by following these steps:
It is a difficult task to try and increase your keyword bank while growing your revenues/profit and managing your cost and risk. Finch can evaluate your AdWords campaign and do what every company wants with their keyword bank -- expand the keyword bank while growing revenues and decreasing costs for your company.
Recently Tim Ash, CEO of Sitetuners, did an interview on Conversion Rate Optimization. Tim is the guru when it comes to Landing Page Optimization and his company can make sure your landing pages are getting the best conversions possible. He said, in regards to companies running AdWords campaigns, that "You need to look at the man behind the curtain, it could be a Wizard of Oz situation. Some pay-per-click management firms in particular, I don't trust their technology, it's still a lot of account rep time. But, there's one specifically, especially for e-commerce.....Finch has really nailed that whole programmatic buying thing for pay-per-click on AdWords." (from the 18:35 mark)
While Landing Page Optimization is important, it is not the only optimization process you can look at in optimizing your AdWords campaign. Traffic, ads and landing pages are three key components in optimizing your campaigns. Traffic optimization is crucial because you want to limit your losses by reducing the spend on money-losing keywords. On the flip-side, you want to boost the the volume on higher converting keywords. This could be a difficult task for companies that have thousands of keywords and not enough manpower to adjust every keyword in the campaign.
The volume of impressions and traffic that is coming through your higher converting keywords will increase your opportunities to test your ads and then will push more traffic to make sure your landing pages are converting. All three parts of optimizing your campaigns work together. If you only are focusing on your landing page and not receiving the best traffic, you will have a difficult time understanding what is the best way to optimize your landing page.
Finch is the pay-per-click management company that has "nailed" the programmatic buying for AdWords. Our free audit will give you detailed information on which keywords are low or high performing and where you should start optimizing. We will tell you what should change and why.
Black Friday through Christmas are the top revenue and profit days for most retail companies. Imagine the hard work a business goes through to prepare for this season:
Now, try to imagine that this same business closed it’s doors daily at 1:30 in the afternoon with customers standing in line waiting to take out their wallets. What?!? It’s beyond comprehension! The results would be devastating to holiday sales.
This is exactly what online retailers are doing with their AdWords sales. You have the products in the warehouse, you have the staff trained and prepared, you have done all the work for your marketing and advertising programs to get the most out of the 2014 holiday season. Are you going to close the door at 1:30 pm every afternoon?
On average, Google AdWords delivers 25-40% of a online retail company’s revenues; you have it configured, setup and tuned so that you can generate as much sales as you can inside your cost constraints. The holiday season starts to ramp and you are seeing the payback from the hard work.
Then Cyber Monday came and by 1:30 pm your daily budget was maxed out. Your ads stopped showing. Your store closed for business on Google during the busiest time of the year! To make it worse, your competitors were still showing their ads and captured all the traffic and the revenue that came from it. Don’t let this happen through the rest of the holiday season!
From the time you give Google $1 for a click until you receive funds from your payment processor in your account from the corresponding sale, it takes 2 days in average. You turn your ad budget into cash from the profit in 2 days. Why on earth would any business owner chose to do limit their budget?
Here are the reasons:
1. We have a fixed AdWords budget; OK, but if you knew that for each additional $20 you give to Google you receive $100 back in profitable revenues… would that change your mind? If the owner of your company or the person approving the budget knew this they would instantly increase the budget so that the company could increase sales, increase profit and increase market share. Please show this blog post with that person.
This captures 95% of clients running out of budgets.
2. All the other reasons not relevant to leaving profitable revenues on the table.
It is our job to maximize revenues and profits for our clients on AdWords and it just kills us to see clients who are growth and performance focused practically lock their front door and shut off the cash register when there is a huge line of customers ready to buy. Act on it before the season is over!
The profit optimization model has the objective of maximizing the overall profit that comes from the Ad spend. The assumptions for this model is:
Each product has varying sales prices and profit margins, and the advertiser wants to maximize the overall profit from the ad spend.
Optimizing for profit is the holy grail of online advertising. It is the only model where you have all the information (product cost, revenues, profit, AdWords cost, etc.) which means you can predict the outcome of the next click before you set the bid for how much you are willing to pay. This outcome is Profit, and as long as your profit increases you are willing to fund the ad spend.
Here is an example:
A company is selling electronics on their web site and their objective is to generate as much profit as possible. They must track the margin (or revenues and cost) for each product or transaction (How to capture profit and link it to AdWords cost). In this scenario the advertiser will keep increasing the ad spend as long as the overall profit increases.
Here is the data to determine the Max CPC:
The Max CPC will be set for each keyword based on the profit history, the conversion rate and the historic Cost. The objective for managing a campaign with this method is to maximize the overall profit.
In a portfolio approach, if you have 1 keyword producing profit contribution at 10%, then another keyword may be producing profit at at 30%, both will gain increased Max CPCs, while a keyword with negative profit will get the Max CPC reduced (assuming all other variables are constant). Because the constant changes competitors for the same clicks makes it makes competing for the best clicks auctioned off by Google every time someone enters the search box to look for something exceptionally dynamic by nature. This requires constant elasticity testing for each keyword to stay inside an optimal range. Each change is measured by impact on profit, driving the decision making for bid adjustments.
This methodology is effective when you have MANY products with the VARYING margins.
Revenue optimization has the objective of maximizing the Revenues that comes from the Ad spend. The assumptions for this model to be effective is:
Each product has the same profit margin
Here is an example:
A company is selling electronics on their web site and their objective is to generate as much revenues as possible. They will either be using Google AdWords conversion tracking (Dynamically tracking the amount of each completed shopping cart with the Value variable) capture the amount from each sale and have that associated with the keyword, ad and ad group that captured the sale (for more info click here).
The company knows that in average they can spend 20% of their revenues on advertising (leaving 80% of the sale to cover product costs, order processing, overhead, etc.). Here is the data to determine the most you can pay for the next click (Max CPC):
Target cost of Revenues: 20%
Last sale recorded for given keyword: $300
Conversion rate: 5%
Max CPC: $3.00
The Max CPC will be set for each keyword based on the revenue history, the conversion rate and the historic cost. The objective for this way of managing a campaign is to maximize the revenues as long as the cost of revenues is 20% in average.
It is important to distinguish that the max CPC is set per keyword (ideally for each match type of the keyword, with bid modifiers for Device and Remarketing for Search profile) based on the keyword’s cost/revenue history, and not based on the price of the product the keyword matches. The reason for this is that once the keyword triggers the ad to display and the potential buyer clicks on it, once on the site the potential buyer may or may not purchase the matching product. He or she may buy something totally different or purchase a number of products. The only hard data you can optimize from is the cost, the revenues, and the conversion rate.
In a portfolio approach, if you have 1 keyword producing conversions at 10% cost of revenues, then another keyword will be allowed to produce conversions at 30% (assuming the revenue produced by the two keywords are the same, and because they usually are different it creates a complexity that is only practical to solve with automation software) . The average of 20% is what matters to maximize the outcome under this methodology. This is easy to illustrate through branded terms. The branded terms (your own company name, url, etc.) usually produces revenues in the low single digit percentage cost because you likely have a quality score of 10 (ad rank impact) and a very high relative conversion rate. That leaves a surplus (relative to the 10% cost of revenue target) that can be used to grow your revenues, market share and customer base for non-branded terms and still stay below your cost target. Alternatively, if you isolate the branded terms to enjoy the high profit those produce, the non-branded terms may all be above 10% cost of revenues and the result is that you leave all that business for your competitors to have.
This methodology is effective when you have MANY products with the SAME margins.
One problem with this model for an eCommerce company is when products have varying profit margins and prices. In theory you can successfully optimize a campaign for Revenues, but while the revenues may grow - the profit may turn negative in a worst case scenario. The solution to this challenge is presented in the next blog in this series.
This is the 2nd post in our series on Conversion Types. Choosing the right conversion type for your business is vital to generate and optimize the value that is returned through your AdWords budget. You can read the first post here.
Historically, CPA (cost per acquisition) is the most common conversion type among businesses in many industries. This model best serves advertisers that are optimizing for conversions that have a fixed value. These conversions could include completing a web form, viewing a key page, phone call, completing a shopping cart, etc. The most important factor to consider when choosing the CPA model is whether each conversion has the exact same value.
The assumptions for this model is:
Every conversion is worth the same, including;
Cost per Conversion
Value per Conversion
CPA is effective for businesses that generate leads which are followed up with offline to buy only one product, at a fixed margin. This approach may also be effective for eCommerce companies that sell only one product at a fixed margin.
However, if your company does not match one of the two profiles above, your AdWords account could be running very inefficiently. If your business offers more than one product at a fixed margin, you may be limiting your ability to compete effectively and damaging the bottom line.
Here is an example:
A company selling electronics on their site with an objective to generate as many sales as possible may have looked at historical performance and learned that the average sale is $100. They can spend 20% of the revenues on advertising, leading to a $20 CPA target. With the $20 CPA target, the Max CPC is calculated in this way:
Target Cost per Acquisition (CPA): $20
Conversion rate: 5%
Max CPC: $1.00
This is the basic approach employed by most companies. The Max CPC will be set for each keyword based on the conversion rate. The primary objective for this approach to managing a campaign is to maximize the number of conversions while maintaining an average cost per conversion/acquisition of $20.
Further, a company could employ a portfolio approach, where a group of keywords could generate an average CPA of $10, while other keywords are allowed to go up to $30 CPA. The overall average of $20 is what matters to maximize the outcome under this approach.
As a reminder, this methodology is effective when you have ONE type of conversions (one product to sell, one web form to fill out, etc.).
If there is variability in the value of a conversion (revenue or profit, for instance), then CPA may not be the right model for your business. For an eCommerce companies that offer many different products, each with different margins, the CPA approach does not take into consideration the total Revenues or Profit being produced by each keyword.
If the purpose is to generate revenues or profit, you must capture and use that data when deciding how much a click is worth. The magic in optimization is knowing the outcome before you buy the click; without historical data (revenue/profit) there is zero probability that you will make the right choice when deciding how much to pay for the next click to maximize your business value. Choosing the right conversion type to optimize from becomes infinitely critical for your success.
Next: the next post will cover how to optimize for revenues, followed up by a post on when to use profit.
Conversions have long been, and will continue to be, your scorecard for success as an advertiser on AdWords. The value you gain from a conversion can be measured in many ways: new customers, transactions, revenues and/or profit. Accumulating and measuring conversions isn’t the secret to growing your performance. Leveraging the conversion data, specifically optimizing your account based on the value of your conversions, is the key to long-term growth and success.
At the foundation of your optimization efforts is identifying the ultimate outcome (i.e., transactions, revenue, profit, etc.) you want out of your account, measuring the value of that outcome, and using the data to continually and consistently grow your performance. For instance, if you want to grow profit, measuring and using the number of new customers (CPA model) may drive you in the opposite direction of more profit.
Over the next few posts I will examine the most common goals for online advertisers and discuss pros and cons for each of them. There is an optimal model for most companies, but my experience is that over 90% of all the online advertisers we talk with want one thing (revenue and profit) but they do not use a scorecard and/or optimization model centered on that outcome.
Knowing what a conversion is worth before you buy the click is foundational to successful advertising execution. This series will define the worth of various conversions and how to execute to maximize that worth. These are samples of conversions:
Completed shopping cart (transaction)
Fill out and submit web form (lead)
View of key page (i.e. online demo)
Download document (i.e. white paper)
Phone call (Call Extension)
Any other action on your site that can be measured
This is easy enough and straight forward for savvy online marketers. If this was all there is to it, we could just put a $ figure to each of these actions based on the value they add to our business and be done with it. For example, every sale on my website is worth $25 to my company because the average sale is $100 and we have on average 25% margins on what we sell. Now assume you have a 3% conversion rate on your site and you can spend $0.75 per click for a given keyword.
In reality this is far more complex. If you have 10,000 products, each with different prices and margins. Now, your average checkout has 2.7 products in the cart. Is each sale worth the same? What about adjusting for mobile clicks, how about return visitors? Is an exact match worth more than a broad match visitor? Herein lies maybe the biggest waste of all online marketing budgets, and more importantly, the biggest opportunity for the progressive advertiser to outcompete everyone else in their industry.
In my 15 years in eCommerce, with the last 5 in the paid search (PPC), I have seen the full spectrum of models to grow sales and drive profits. As I write this in November 2014 on the eve of the holiday season kicking into gear, most companies are using the same measurement of success today as they did 10 years ago. Additional complexity has been added, such as analyzing attribution relationships. But if the added complexity does not have a relationship to the ultimate outcome (profit), then it’s simply added complexity without benefit and cannot be leveraged for growth. Back then very limited data was available compared to being able to track almost anything today: the number of conversions they can generate at a set cost per conversion (CPA) is the measurement of success and means of executing their AdWords programs.
When everyone does this it creates an incredible inefficiency when competing for the most profitable clicks you can buy from Google. What if there was a much better way? What if you knew exactly what the next click from Google would give you in return (revenue and profit)? Would that change how you run your AdWords program?
In this series I will cover how to do this for a variety of business models, from businesses generating leads to profit optimization for large eCommerce sites. I will cover these models and the scenarios they are best fitted for:
Conversion optimization: Cost per Acquisition (CPA)
Revenue optimization: Cost per Value (CPV)
Profit optimization: Total profit objective