Bid Management Misunderstanding #2: “Bid Rules”
“Rules based bidding is a disaster!” PPC Expert 1
“Are you nuts? Bid rules are essential!” PPC Expert 2
As with the question of Automated Bidding, it turns out both of these folks might be right depending on what they mean by “bid rules” — a loaded term if ever there was one.
Rules-based bidding earned a lousy reputation in the early days of PPC and for good reason. The types of rules varied wildly from the rudimentary to the complex but suffered conceptually on two different grounds: they were generally based on hunches rather than data, and they were often position-based. Rules often looked like:
- Bid $1 if the KW hasn’t had an order and has spent less than X. Turn it off if it’s spent more than X with no orders. Bid $2 if its had an order and its cost to sales ratio is good. Yadda yadda.
- For this group of KW Bid to position 3 if it’s less than $2; if its more than $2 for position 3 take position 6 no matter what it costs. For this group of KW…
- Bid to position 3, unless position 2 is within 5 cents then bid to position 2. If position 4 is within 2 cents (bid jamming) and we could save more than X% by dropping to position 4 then do that…and on and on.Very clever ways of playing the game badly.
or, the pinnacle of rules based bidding: the open auction games:
In addition to bidding by hunch rather than data, and letting competitors dictate your CPCs by playing position games, rules-based bidding also frequently involves another poor practice: factoring in sunk costs.
Let’s say you’ve just assumed management of a program badly managed by someone else. All things considered you’re aiming for break even profitability. For a given KW, the previous manager spent $10,000 on 10,000 clicks which drove 100 orders and $5,000 in margin. Horribly inefficient, yet the answer isn’t to turn it off, it’s to realize that if 10K clicks drives $5K in margin you can only afford to spend $0.50 per click going forward. The fact that you’ve lost $5K on that term already is irrelevant. The CFO may go berserk wondering why that bad KW is still running, but the answer is: the traffic is valuable…not as valuable as the other person thought, but it does have some value.
Bidding smartly involves predictive modeling. The goal is to determine what the value of the traffic driven by each different ad is likely to be and then set the bid to the fraction of that value you’re willing to spend on marketing. The best foundation for guessing the value of the traffic comes from the data you’ve observed at the most granular level possible. This gets complicated as the data gets thin, and requires some fancy stats on the way different attributes of the ad (the keyword, product category, sub-category, manufacturer brand, match type, etc) are likely to impact the value of traffic. The algorithms can be incredibly smart, and can involve as many checks as you want: “Don’t change a bid more than X or don’t bid more than Y without human review” whatever.
However, while bidding based on observed past performance is necessary, it is not sufficient by itself. Oftentimes the smart analyst knows that something is about to happen that will change the performance of a KW or collection thereof in ways that no algorithm can predict, or react to quickly enough.
A big sale is happening on wide screen TVs next week. This will impact the conversion rate, the AOV, the margin %, etc. all of which impact the value of the traffic. The algorithm will figure this out eventually, but is likely to react after the sale is over, missing opportunity on one side and wasting money on the other.
Enter the smart type of “bid rule”. The analyst can say: “Past experience indicates that during a sale of this magnitude the value per click changes by X%, so I want to lift bids by X% during the sale to capture more traffic without sacrificing efficiency. And, after the sale is over, the algorithm is going to crunch on data that is somewhat inflated by the sale effect, so I might have to push the numbers generated by the algorithm down a fraction to stay within the target.”
These types of rules overlays are essential in retail advertising to account for short term offers, fluctuations in stock levels, seasonal effects (Does the algorithm know which Friday is Black Friday, or when your shipping cut-off for Xmas delivery is? or what the July birthstone is?), etc.
Agencies without these rule overlays invariably underbid at the beginning of the Christmas rush and waste money after Xmas is over — we’ve seen the data, over and over again.
So are bid rules good, or bad?
It depends on what you mean by rules!