Keyen Farrell started his career by creating a successful network of e-commerce websites which awarded visitors with cash rewards and rebates.

In 2007 he graduated from Maine’s Colby College summa cum laude with a degree in Economics, and a concentration in Finance Markets. He has also devoted much of his energy since 2001 to the Connecticut chapter of the Special Olympics. Sailing  is a passion of Farrell’s, and as Special Olympics coach he teaches the joy of competitive sailboat racing to athletes with intellectual handicaps.

Keyen Farrel was hired into the Web Publishing division of Google in September of 2007 as Account Strategist. For a year and three months he worked in this department alongside clients like Us Weekly, Martha Stewart Living, Consumer Reports, Rolling Stone, and Ancestry.com. In January of 2009 he began work in the Media and Entertainment advertising vertical, continuing his work  as an Account Strategist—a job he has excelled at.

He manages a paid search portfolio that is ranked third amongst the Media and Entertainment advertisers by spend. He currently serves as the lead Account Strategist to ABC, NBC, and CBS on the east coast. The New Hire Training, Google Grants, and AdWords Editor programs have all benefited from his input as well.
More Resources:

Keyen Farrell :: Home Page
Keyen Farrell :: Article on Betaflow
Keyen Farrell :: Listed on Review-inc.com
Keyen Farrell :: Information on Incprofile.com
Keyen Farrell :: Article on 800review.com
Keyen Farrell :: Article on 4WorkLife

This is usually a fool’s errand, but I’m going to make an incentive marketing prediction for 2011. I, Keyen Farrell, believe that the rise of freemium content will open sizable opportunities for incentive marketers. Freemium content will continue to grow, and incentive marketers will have opportunities to sweeten the deal for consumers. Key to the success of incentive marketers will be two things. First, it will be their ability to hone in on which content a user is most engaged with. Second, will be their ability (or inability) to provide an incentive that entices that particular user. It’s an age old issue with incentive marketing, but fremium content will require an incentive that is as suited to the client as the content they are preparing to pay for. Incentive marketing aside, the rise of freemium content is by itself really interesting. The site Freemium Content provides good commentary on the debate around this burgeoning model.

It still surprises me how many incentive marketing & cash back websites maintain minimum payout thresholds. In a space where trust is paramount, payout thresholds destroy credibility. If users must accrue $10 or $20 in rewards before seeing those earnings, many will invariably hit the eject button. Site owners mostly use payment thresholds as a means of withholding payouts from low-earners under the guise of covering transaction costs. The transaction cost argument no longer holds water given the efficiencies of bulk e-payments. PayPal mass payments cost a mere 2%. If you choose to go the snail mail route and cut paper checks, your costs will be astronomically higher. I, Keyen Farrell say, “Don’t do it!” Unless you are operating at enormous scale (think Ebates,  NetFlip circa 2002), or have unusually lucrative offers, the price of cutting checks is simply too high. Keeping your transactions purely electronic will save you time and avoid needless headaches for you and your users. You can even designate a single bank account into which commission revenue flows and from which incentive payouts are drawn.

If you follow the Zero-Threshold Rule, your visitors will be inclined to complete more, not less offers on your site. You may find that users complete one or two offers to test it out. Yet once you hold up your part of the bargain, they will almost always return. The Zero-Threshold Rule builds trust with your users and should not be ignored as a selling point. You can further leverage the rule by working it into your site’s messaging. It’s astounding how many incentive websites have not only minimum payout thresholds, but bundle offers together, forcing users to complete several offers at one time. Bundling offers is the antithesis of the Zero-Threshold Rule and not only destroys your user base but compromises the quality of transactions. Sustained incentive marketing rests upon happy users and happy merchants. The last thing you want is low-quality, chargeback-prone transactions caused by bundled offers. If your site contains a varied selection of offers, and users are given the flexibility to complete which offers and how many, everyone comes out on top.

One of the toughest questions facing an incentive website or any e-commerce website for that matter, is the question of price. In the case of the former, price refers to the size of the cash reward (rebate) offered to users. The goal is to size the rebate such that it maximizes net income. If the goal is to maximize ROI, this sweet spot is critical. And if the goal isn’t to maximize ROI, there are probably greater things to worry about.  :)  Most incentive marketers will size their cash rebates based on trial and error, but there’s a far more precise way to determine the optimal rebate. The following is a walk through of how to solve for the optimal incentive rebate.  Using some high school algebra and calculus. I applied this technique to determine optimal rebates for the network of incentive websites I created in 2003. This technique allowed Topaz Financial to drive more than 100,000 completed advertiser actions at margins that would not have otherwise been possible. If the math looks daunting, there are many tutorials for solving these equations. A search for ‘solving systems of equations’ and ‘differential equations’ should turn up helpful resources.

To illustrate how it works, let’s create a hypothetical situation. We’ll assume that your incentive website offers a cash rebate for each completed action, in this case, the purchase of a pair of shoes. Further, let’s assume the merchant pays you a $25 commission for each completed sale. We want to determine the size of the cash rebate that maximizes total profit. Your first inclination might be to offer visitors a large share of your commission to entice a greater number of users to complete the purchase (action). Yet paying out a large share of the commission could cause the reduction in net income that outweighs the increase in volume of actions. On the one hand you want to offer a rebate that entices a large number of visitors to complete the offer. On the other hand you want to offer a rebate small enough to keep your net commission high. Likewise, there is a positive relationship between the size of the rebate and volume of actions completed. To make the math simpler we will assume that this positive relationship is linear. In other words, we will assume that a given change in the rebate will always induce the same increase in purchases. Admittedly at extremely high or low rebates this assumption may not hold, but for our purposes it is a fair assumption.

To start, we need to collect a few data points. You’ll need to experiment to see how users react to a few different rebates. The benefit of the linear assumption is that we only test 2 prices in order to calculate the slope of our line.

Assuming the offer is currently running, you already have one set of coordinates. Let’s assume that when an offer has a rebate of $5 there are 15 completed actions. To find the second set of coordinates you’ll want to set a new rebate and measure the number of completed actions. Let’s say that when we increase the rebate to $10, there are 40 completed actions. To put it in math terms:

Let us denote pairs of shoes sold as Y and rebate as X.

The equation of Y in terms of X is a linear function of the form Y = A + B X, where A and B are constants.
This equation passes through (5,15) and (10,40)
Thus,
15 = A + 5 B Equation 1
40 = A + 10 B Equation 2

Subtracting Equation 1 from Equation 2,

40 = A + 10 B Equation 2
15 = A + 5 B Equation 1
25 = 0 + 5 B

Or B= 5 =25/5

Substituting the value of B in Equation 1,

15 = A + 25
or A = -10 =15-25

Thus, the equation is of the form
Y = 5 X – 10
where X is the reward and Y is the number of shoes sold

We have to maximize profits Z= (Commission-Rebate) x Number of shoes sold= (25-X) Y
but Y= 5X -10
Therefore,
Z=(25-X) (5X -10) = 125 X -250 – 5 X^2 + 10 X = O r Z= -5 X^2 + 135 X -250

Our task is to maximize profits or maximize Z= -5 X^2 + 135 X -250
To find the maximum value of Z we differentiate Z with respect to X and equate it to zero:

dZ / dX = – 10X +135=0
or X = 135/10= 13.5

Thus to maximize profits, the rebate should be 13.5
Profit = Z= – 5 X^2 +135 X -250 = 661.25

Since  a rebate of 13.5 would mean selling a fraction of pairs, we can offer a rebate of 13 or 14 which would give an identical profit of $660 (see table).The most challenging part of the process is holding the traffic sources and number of clicks to the offer constant while you are testing. If there are huge swings in the number of users exposed to the offer, or if the composition of traffic changes drastically, your results will be less trustworthy.