The standard pricing model for email marketing — the CPM — may soon change. Industry consolidation, commoditization, and growing data volumes threaten the standard. Buyers may soon confront models that range from a platform license (all-you-can-email) to total utilization (data + messaging) to seat-based models. In November, I will publish research into the rationale for model changes, evaluate different candidate models, and explore the repercussions of the change.
I need your help. Price changes will have dramatic and difficult to predict effects on customer experience, marketing practices, the vendor landscape, and even the structure of the marketing organization. For example, an all-you-can-email model may, paradoxically, reduce email volumes in the long run, if it removes barriers to adoption of cross-channel programs.
This potential shift from channel-specific to cross-channel is one of the more interesting consequences of a model change. I’d like your reactions include:
What is the best pricing model given the challenges you face (performance, cross-channel, real-time, mobility, etc.)?
Who in your organization might be affected by the change?
How do you anticipate the purchase process (RFP, selection, negotiation, contract review) might change as a result of a model change?
If you faced no pricing limits on email, how would your strategy and operations change?
If vendors moved to a platform model — e.g., including other modules such as web recommendations, push notifications, or behavioral targeting with email — how would your strategy and operations change?
I recently received a direct mail piece from one of my favorite retailers with a massive ad in that proclaimed "We Beat Internet Prices." Now, I am a big fan of straightforward and robust value propositions, but these types of brand exclamations are antiquated and add little value to customers, mainly because they simply reward customers for being good bargain hunters. Instead of simply stating you beat your competitor’s prices, employing strategic pricing and customer engagement initiatives creates real distinct value to your customers by:
Showing them you can execute on your low price promise and not just talk about it. Employing a holistic pricing strategy meets your customer’s price expectations can indicate to your customers that you are truly ‘walking the walk’ when it comes to offering the lowest price.
Building your credibility. Understanding your customers’ needs and offering solutions that facilitate decisions and generate engagement builds credibility. Simply shouting that you match Internet prices does little to build credibility with your customers.
Helping them with real problems. Shoppers don’t need guidance on finding the lowest price -- they need to understand how your brand and solution help them compared to your competition.
The lines are blurring between software and services — with the rise of cloud computing, that trend has accelerated faster than ever. But customers aren’t just looking at cloud business models, such as software-as-a-service (SaaS), when they want more flexibility in the way they license and use software. While in 2008 upfront perpetual software licenses (capex) made up more than 80% of a company’s software license spending, this percentage will drop to about 70% in 2011. The other 30% will consist of different, more flexible licensing models, including financing, subscription services, dynamic pricing, risk sharing, or used license models.
Forrester is currently digging deeper into the different software licensing models, their current status in the market, as well as their benefits and challenges. We kindly ask companies that are selling software and/or software related services to participate in our ~20-minute Online Forrester Research Software Licensing Survey, letting us know about current and future licensing strategies. Of course, all answers are optional and will be kept strictly confidential. We will only use anonymous, aggregated data in our upcoming research report, and interested participants can get a consolidated upfront summary of the survey results if they chose to enter an optional email address in the survey.
Aside from my work with product strategists, I’m also a quant geek. For much of my career, I’ve written surveys (to study both consumers and businesses) to delve deeply into demand-side behaviors, attitudes, and needs. For my first couple of years at Forrester, I actually spent 100% of my time helping clients with custom research projects that employed data and advanced analytics to help drive their business strategies.
These days, I use those quantitative research tools to help product strategists build winning product strategies. I have two favorite analytical approaches: my second favorite is segmentation analysis, which is an important tool for product strategists. But my very favorite tool for product strategists is conjoint analysis. If you, as a product strategist, don’t currently use conjoint, I’d like you to spend some time learning about it.
Why? Because conjoint analysis should be in every product strategist’s toolkit. Also known as feature tradeoff analysis or discrete choice, conjoint analysis can help you choose the right features for a product, determine which features will drive demand, and model pricing for the product in a very sophisticated way. It’s the gold standard for price elasticity analysis, and it offers extremely actionable advice on product design. It helps address each of “the four Ps” that inform product strategies.
Product strategists struggle with the issue of value all the time: What constitutes a revenue-maximizing price for my product, given the audience I’m targeting, the competition I’m trying to beat, the channel for purchase, and the product’s overall value proposition?
There are tools like conjoint analysis that can help product strategists test price directly via consumer research. However, there’s a bigger strategic question in the background: How can companies create and sustain consistently higher prices than their key competitors over the long term?
The Mac represents a good case study for this business problem. Macs have long earned a premium over comparable Windows PCs. Though prices for Macs have come down over time, they remain relatively more expensive, on average, than Windows-based PCs. In fact, they’ve successfully cornered the market on higher-end PCs: According to companies that track the supply side, perhaps 90% of PCs that sold for over $1,000 in Q4, 2009 were Macs.
Macs share common characteristics with Windows PCs on the hardware front – ever since Apple switched to Intel processors about four years ago, they’ve had comparable physical elements. But the relative pricing for Macs has remained advantageous to Apple. At the same time, the Mac has gained market share and is bringing new consumers into the Mac family – for example, about half of consumers who bought their Mac in an Apple Store in Q1, 2010 were new to the Mac platform. So Apple is doing something right here – providing value to consumers to make them willing to pay more.
Cloud computing, on-demand solutions, subscription fees… software licensing is undergoing significant changes. Enforced by the current economic crises with tight IT budgets, companies don’t have the money to pay upfront licenses and are reluctant to take financial risks over many years when purchasing software. A key factor of the current growth of cloud computing is its financial benefits: no capital expenditures, no upfront financial risk, no depreciation and nothing on the balance sheet! But pay-by-use licensing models are not necessarily limited to cloud deployment models and can be applied to more traditional implementations as well.
Traditional software licensing with upfront payments has served vendors well over the last 40 years. However, over time vendors had to face significant disadvantages as well. The pressure to successfully close quarter by quarter and the fiscal year has led to a common practice by customers to push decisions until year end for a special deal. Discounts up to 80% became not uncommon in the software business. Another problem is the revenue volatility in difficult economic times. In 2009 many software companies had to face a decline in new license revenues of 10 to 25%. Without the constant stream of maintenance revenues many software companies would be facing severe financial problems today.