Does a Profit Maximization Strategy Make Sense For Your PPC Bidding Optimization?

Does a Profit Maximization Strategy Make Sense For Your PPC Bidding Optimization?

Having a focused and defined strategy is a necessity – not a luxury – in the modern era. Especially when you consider the numerous interactions that you can track and attribute directly to specific campaigns and ads. Strategy nowadays is often best determined by the data that is actually captured and plugged into your decision making. While all digital marketing provides powerful data, the best channel for tracking data across the entire funnel – from impressions to conversions – is Paid Search. Perhaps not surprisingly, then, the bidding strategies that produce the best results come from data that illuminates outcomes (conversions or revenue) attributed back to the ads, keywords, and the clicks that drove them. Thus, a successful digital marketing strategy also incorporates new and innovative paths for maximizing profits as much as humanly possible.

Defining Your Goals

Profit Maximization Strategy: first, define your goalsWhen it comes to SEM, most advertisers focus on either conversion- or revenue-related goals, depending on the needs of the business. Why focus on revenue goals? Simply put, using revenue data for modeling and bidding is one of the best ways to generate returns on ad investment. While revenue data from online transactions are immediately available for some businesses, other teams are able to put latent or offline revenue data to use for optimization.

But why focus on conversions? Focusing on conversions can be meaningful for bigger types of online purchases or subscriptions. This is especially pertinent in scenarios where revenue data tracking isn’t available or has integrity issues.

Ultimately, the best tangible data that maps to meaningful ad-click outcomes for your business is probably the best indicator regarding the type of strategy your program needs.

While every bidding strategy has its benefits, one gold nugget revenue-focused method called Profit Maximization stands out. In Paid Search, it’s pretty straightforward: maximize profit dollars. It focuses on this specific revenue goal without another restraint, allowing two notable outcomes:

  1. The strategy is able to yield the best absolute profit figures possible, however:
  2. There is often some decrease in total volume due to the bidding decisions.

What’s special about Profit Maximization? It’s done at the individual keyword level, so every keyword either drives maximum profit, or it doesn’t enter the bidding war. This is a really big opportunity for the right businesses.

Where to Use Profit Maximization Strategy

“ProfitMax” is a powerful goal to bid toward in PPC because of its business impact for certain types of organizations, which see significant lift with the new model. In particular, we’ve found a few business categories that will transition well to the benefits of a profit maximizing bid strategy:

Lead Generation

The Lead Gen teams are creating business opportunities for others, and charging for it, which creates an opportunity to focus on PPC-driven profit margins. These lead generators may not have inventory concerns, brand recognition concerns, or market share goals, which is notable insofar that volume has the potential to drop with this strategy. Therefore, it might make sense to allow some decrease in total volume with the aim of increasing profits for these companies!

Intermediary Transactions

Other intermediary-transaction business models – like “arbitrage,” promoting subsequent impressions and clicks – have a slimmer profit margin, so maximizing that margin based on data could have a dramatic impact on business.


Other types of businesses – for example, those running eCommerce sites – are candidates for this type of model because they have a regular stream of revenue data in place from online transactions, coupled with low profit margins some of the time. If a decrease in overall volume isn’t at odds with other goals, Profit Maximization can make a big difference on these campaigns as well.

Are you in a B2C Marketing organization that generates a high quantity of Leads with PPC?

Do you track and store revenue data from ad-clicks, whether offline or online? If you haven’t tested this methodology, you may have a significant amount of potential profit missing from your bottom line.

With a normal revenue focused portfolio optimization strategy, you could spend $100,000 and earn revenues of $120,000 — a $20,000 profit margin. With a profit maximization strategy, you may lower volume and spend $70,000, but return $100,000 — a $30,000 profit margin.

How Does Profit Maximization Strategy Work?

So, how does one execute a strategy to bid toward a profit maximization goal? This sort of optimization requires quite a few elements to align:

  • revenue data collection
  • revenue data integration
  • strong processing power
  • revenue-per-click keyword modeling
  • natural language processing for long-tail keywords
  • thoughtfully analyzed bid landscape data
  • scalable and flexible cloud infrastructure
  • keyword-level bidding optimization
  • elegant machine learning algorithms,
  • a data-science based mindset

In short, it’s a complex solution to build. Since all of the calculations, bidding, and optimization effort needs to happen on every keyword, two of the important enablers include:

  1. Sharing data between keywords so there is sufficient information with which to make accurate decisions, and
  2. Infrastructure that allows the modeling to run at scale.

The data enablers come from powerful integrations with any revenue source, along with Natural Language Processing to help share data between similar keywords. The infrastructure hosts a load of transactions and interactions to meaningfully function and protects against possible anomalies.

Ultimately, the secret sauce of the Profit Maximization bidding optimization strategy lies within the deployed algorithms. These algorithms model and calculate the right bids that maximize the goal at hand – and then automatically execute on those calculations.

Each keyword must fight a battle to hit the profit goal, and the concerns of the overarching program take a backseat to keyword-level profit concentration. This contradicts the go-to bidding optimization methodology of the last 10 years: portfolio bidding. Portfolio bidding emphasizes an overall maximization of, say, revenue, but only as long as an efficiency metric is maintained. The result: many keywords couldn’t be bid towards profitability – selective under-performance is built into the model. When you remove this barrier and refocus the algorithmic goal on profits, you’re able to significantly improve that metric.

Because of the barrier-removal, volume often sees a drop upon a strategy switch; however, it results in powerful algorithmic decisions being made on every keyword that only drive clicks leading to conversions with the highest potential profit. Historical data is important for propelling the strategy, but  it’s not as important as having organized, fresh, and integrated revenue data – whether online or offline. When you integrate deep funnel revenue data into the right AI-powered machine, profit-focused bidding decisions for your programs (and business) can be achieved.

Profit Maximization Strategy: Predicted Margin by CPC

What’s Next?

Okay, so maybe this is the right type of solution for your business, or at least worth testing – but how do you get started? Some of today’s technology is able to handle this level of data-driven optimization. The PPC bidding optimization tools currently on the market have strengths and weaknesses, but one technology partner stands out when it comes to running a Profit Maximization bidding strategy: QuanticMind. Its aptitude in data science modeling and algorithm-building; an infrastructure designed for unlimited scale and anomaly handling; a business focus on peak paid search performance; differentiating with its ability to collect and integrate data from any source – all these components align to work toward technical revenue goals. When you introduce your deep funnel revenue data into tested QuanticMind algorithms and scalable infrastructure, your profit maximizing optimization dreams turn into reality.

QuanticMind has been able to move the needle significantly for many businesses that want to switch to a profit maximization focus, but bear in mind that not every organization benefits from this. The method is very powerful, and worth testing for many organizations – but because of its impact, it needs to strongly align with the paid search goals. Ultimately, you have to scope your program with an expert to understand if focusing on this class of SEM methodology suits your business. Talk to a Solutions Engineer to see if this bidding strategy has potential for your Paid Search goals.