Digital Commerce Principles
If you’re new to the e-commerce industry, you’ve likely noticed that there’s a dearth of writing on the fundamentals. There’s no single “101” tome that professionals can point to; instead, there’s a lot of great writing on disparate topics within the space (such as UX/UI design and development, merchandising, analytics, and digital marketing), and some amazing reporting from writers like Brad Stone, Jason Del Ray, and Sapna Maheshwari. The growth in popularity of e-commerce as a retail modality, and the splashy headlines we see about Amazon or DTC-only brands such as Warby Parker, belie the reality that the industry is less than 30 years-old and accounts for just 13.4% of total retail revenue in the U.S. While maturity will likely accelerate in light of the global pandemic impetus, the industry is still maturing, which is to say that practitioners pull from a wealth of other disciplines in order to inform their strategy and operations.
Inspired by Ray Dalio’s “Principles,” I have pulled together a series of observations and lessons I’ve learned over my cumulative years of working in digital commerce. I am constantly stress-testing and adding to them by running decision-making through the lens of these principles, and seeing if the logic continues to hold up. In that vein, all new principles have begun as hypotheses, statements, or assumptions that only solidify through real world application.
Whether you’re new to the e-commerce space or a seasoned practitioner looking for a model through which to make a critical decision, I hope that these principles can help to scale your problem-solving and guide your outcome.
Product Management
All value we attempt to create is “assumed value” until we release an experience, feature, or service to users. Our users will quickly tell us whether or not it’s valuable by voting with their behavior, which should be fastidiously measured
We don’t make decisions because of personal opinion, taste, or convictions. All work should start out as a hypothesis, with a firm understanding of the change we’re trying to make and the KPI the change will impact. These assumptions can be backed up by competitive research, our own analytics, user research, A/B testing, or some kind of quantitative reasoning
We value what users do (observed through our own data analysis, A/B tests, or other engagement signals) above what users say they’ll do often captured in consumer research, feedback, and other qualitative work. (This isn’t a slight to more qualitative research, which can play a critical role in exploring the white space of an experience before getting into more rigorous quantitative testing. Qualitative helps us make trade offs and round out experiences, while quantitative helps us validate a direction)
There’s an opportunity cost to everything we do. We carefully consider allocation of our time (especially for technical resources), considering it as carefully as we do allocation of dollars (if not more so). This is true for both discovery work and implementation work
An X% lift at the bottom of the funnel will have the same impact on transaction growth if it occurs at the top of the funnel. A 5% lift to cart rate or checkout completion rate, will always net out to an equivalent lift in conversion rate, assuming the opposite end of the funnel remains consistent (which it almost never would in a real-life scenario, but this can be used for thought exercises and business casing)
We fully embrace the power of the cloud for every business function, feature, or capability that’s not unique to our business. When considering buy v. build, we opt to buy
Business Cases
If a project requires over 40+ or cross-functional resources (i.e. a self-contained team can’t complete the work on their own), then you should develop a business case
Business cases must demonstrate revenue impact or cost savings, including year one incremental revenue, contributed income, cost (including people cost and incremental opex), and profit. Business cases should be stack ranked for total incremental profit and prioritized accordingly
All business cases should be based upon a hypothesis or underlying assumption for how the project will deliver value to users. The way we measure value is through impact to a KPI. The business case should draw out the relationship between the impact on that KPI and revenue
User Experience
When building user interfaces, we should always favor recognition versus recall in our design language and interactions. That is, users should understand how to engage with an experience intuitively; never force users to recall how to engage with an interface based on memory or past experience. Put simply, interfaces should be easy to comprehend and should not necessitate learning or re-learning how to navigate key aspects of an experience
We should always display as much content as a breakpoint permits, as opposed to hiding content behind an interaction or other device that forces recognition or additional effort from the user to access the content
Consumers that purchase premium products would prefer to purchase those products directly from the firm that creates them in order to have an experience that rationalizes the higher price point (prices being equal within the marketplace). In order to capitalize on this, brands must build intuitive interfaces and experiences that resonate the brand and provide on the “pay off” of the purchase to the customer (call this the “law of Apple”)
Behavioral targeting in experience design will always yield larger impacts than design-thinking that focuses on demographic and psychographic traits
The biggest opportunity in branded commerce in an age of Amazon is depth in a vertical. Amazon has neither the time nor the inclination to build the long tail around niche experiences
Testing
In A/B tests, large framework changes will always have a greater impact on test results than smaller elemental changes to an experience. A paradigm shift that challenges the true white space of a test hypothesis will have a greater impact. Netflix pioneered this notion early on with their practice of “designing to the extremes” in their testing and personalization efforts
The things we disagree the most about are the things that we should always A/B test. Our biggest disagreements often yield the most impactful, fascinating results
Decision-Making
We should never believe in anything that we either lack sufficient evidence for or that we haven’t diligently investigated
In our interactions with our team, peers, and colleagues, we optimize for inspection versus advocacy, where Inspection = sharing our perspectives and reflecting an openness to hear others so that the process thrives on emergence of new information and contribution from all voices, while Advocacy = coming to the table with a predetermined end in mind and a combative and unbending attitude in seeing that end through
We don’t engage in defensive decision-making. That is, we make decisions that have the best outcome for the company, not the decisions that look the best, or reflect the best on us individually, or as a team. Status quo decisions often have very little upside, and we foster a culture that enables us to take greater risks
As you’ll likely note, most of these principles are pulled from other discipline areas. E-commerce essentially re-imagines traditional retail while borrowing from usability design and research, software development, analytics, digital marketing, and project management methodologies. If you’d like to add to the list, or propose an amendment, please reach out.
