A Blessing & Curse for Marketers
The concept of paradox of choice tells us that more options presented in the decision-making process has an adverse effect on both the process and the outcome. Common symptoms of paradox of choice include:
- A slower, more resource-consuming decision process
- Greater apprehension and lower odds of conversion (analysis paralysis)
- Higher expectations of product/service after converting
- Lower satisfaction upon receiving product/service
This paradox is one of the first topics taught to marketing students, but (paradoxically, of course) is one of the most counterintuitive concepts to actually apply to marketing. Incentivized by sales, revenue, impressions, etc. the marketer is used to the notion that more is always better. More leads should equate to more conversions. More products should incentivize better selections and sales opportunities. More budget should translate into more earned revenue. All of these assumptions operate under the notion of a static conversion rate. For instance, if a marketer runs a campaign with an audience of 10,000 prospects exposed to a dozen products or messages and it yields $1,000 in revenue, then the marketer assumes that doubling the size of the audience and providing twice as many products or messages that the output will be $2,000 in revenue. Despite the fact that, paradox of choice tells us this won’t be the case, this is a very difficult idea for marketers to accept.
One glaring example of marketers improperly navigating the paradox of choice concept can be found in product recommendations. For the past several years, an emphasis has been placed upon the benefits of leveraging recommendation engines like that found within Marketing Cloud Personalization (MCP) or Einstein Recommendations (fka Personalization Builder or Predictive Intelligence), to automate content and product recommendations in (near) real-time. These can often be an effective way to educate, engage, and personalize an experience for a potential customer. The recommendations are driven from logic based on criteria such as business rules, content rankings, product categorizations, and customer affinities. One thing that may be noticeably missing from the above criteria is the logic of if or when to apply logic for recommendations. Many marketers leveraging this capability may apply it to their website’s product detail pages and checkout pages. When a potential customer engages with a product on one of these pages, eager marketers tend to salivate and see this as a key opportunity to cross-sell, up-sell, and maximize the revenue conversion opportunity.
These recommendation engines serve content areas and messaging such as:
- “Here are similar items you might be interested in”
- “Do you want to add the following accessories?”
- “Other popular items include…”
- “People who viewed this product also viewed…”
- “Check out these sale items”
At this point in the process, the overload of products and information can often have the unintended effect of instilling analysis paralysis and halting the potential conversion. Yet subsequently, marketers marvel at the nearly 70% abandonment rate of e-commerce checkouts and are floored by the question of how the consumer can be so irrational as to exhibit a clear interest in a product, and then fail to complete the pursuit of it. Perhaps the question should not be why this is irrational behavior on the part of the consumer, but rather what are marketers themselves doing to instill hesitation on behalf of the consumer?
Inundating the shopper at his or her decision point with a multitude of additional products and competing options is a textbook example of paradox of choice. The introduction of more decision-making criteria decreases the likelihood of garnering the conversion. Instead of nurturing and progressing the opportunity, the noise of added products and content may serve to alert consumers as to how many more options and research are to be considered, and just how unprepared they are to make the decision to buy. And even if the customer does convert, then the additional options, time invested, and research spent on the process will lead to higher expectations and, consequently, lower satisfaction with the product they’ve just purchased.
So what is a marketer to do? The suggestion is certainly not to discard the advantages and insights that MCP or Einstein Recommendations can offer during the shopping process. Rather the focus should be to apply the advantages of personalization and recommendation more appropriately. Consider the behaviors and lifecycle stages of the shopper. Are they moving quickly and decisively, perhaps being referred to the site from a purchase-intent traffic source (like ads on a commerce site)? Then it may make more sense to provide their desired conversion experience with less friction from high volumes of additional content, so consider applying rules based on behavior or traffic referrer. Are they browsing and looking for educational material to make a more informed decision? In this case, it makes sense to provide relevant but succinct information based specifically on their search. Keep the context in mind as well; ensure that product pages are not displaying recommendations for competing brands or lower-priced options. If it is determined (due to valid testing, of course) that recommendations will add value on the cart or checkout page then be sure that the types of recommendations do not detract from conversion (for instance, low-cost accessories as opposed to alternative items that may cause shoppers to regress in their conversion process).
Recommendation engines, product or feature options, and educational content can be valuable tools. But they’re not always relevant or helpful to all consumers and all contexts. Sometimes less (choice) is more (value)