How Brand, Product & Community Influence Intention
In my last post I wrote that all user intentions can be boiled down to one of two goals, discovery or recovery. To create marketing strategies for these intentions we must begin by understanding the way users think in the course of trying to achieve these goals.
Users respond to what they know. This can be a positive response or a negative one. This is because there is an existing history that has created an emotional connection. From experience I have found there are some consistent marketing messages that are highly effective at leveraging this connection and driving engagement and conversion metrics for both recovery and discovery goals. These are:
There is nothing new here. These are the same messages and content consumers have always responded to. What is important to note is that the user interactions between these messages and emotions created by them help users complete their goals and move down-funnel to purchase or consumption. Let’s explore these a little deeper.
Brands are instantly recognizable. Brands elicit emotions. Users understand brand without needing more than just reading the name or seeing the logo. It is this instant recognition (more on bridging the gap of recognition) that gets users to take an action and gets them one step closer to their goal. We have done many tests on product messages against brand messages. They are always fascinating. If we look at engagement metrics brand will often (but not always) beat product by a wide margin for CTR, TOS, PV and other engagement metrics.
Products are the lifeblood of commerce. They should not be thought of though as strictly retail or lead-generation. Publishers should think about their content as products merchandise accordingly. Products, their price and often times the features inherent or not present in the product are the final points of consideration prior to purchase. Just as brands drive engagement metrics products drive conversion metrics. RPV, CR, AOV are usually (but not always) way higher when products are featured over brand.
Every marketer knows nothing can help a business or hurt it like word of mouth. The power of this to influence online behavior has been evident since the early days of eBay feedback, Amazon reviews and has flourished into a full-fledged business model with folks like Bazaarvoice and PowerReviews. Of course, this now extends to Social Media. There are a number of highly effective strategies to harness this power on site or even in your ads (which for some reason I hardly ever see). Users love “most popular,” “most read” and “top sellers.” These are the no brainers but there are more strategic ways of using community across the media, in ads and onsite that can help users. It’s also important to think about when and where you deliver these messages to make sure they are contextually relevant and don’t raise considerations to users that may be ready to purchase.
So where are we?
• Users respond very well to brands at the initial stages of consideration (discovery)
• User response moves from brands to products at later stages of consideration (recovery)
• Users rely on community to help achieve both discovery and recovery
Apart from the testing data I’ve seen that helps validate this it makes sense when I think of numerous qualitative examples. Think of the car shopper. For auto, brand is a huge consideration driver. Electronics as well. In fact, with the numerous models of products for many people it’s almost impossible to begin consideration on the product level. I would also venture to guess that there is more final consideration at the point of purchase within brands (what 42” Panasonic HDTV should I buy) than between brands (do I buy the Panasonic TH-42PX600U or the Samsung HP-S4273). Hmm, sounds like a good test idea.
This dynamic, the interaction of brands and products in the purchase funnel, is one of the largest and most interesting questions facing marketers. It is present in a big way in Search. It likely drives much of CTR in display and is a huge part of on-site behavior. Likely the answer will vary by vertical. It may vary by demographics. It may also be different for different businesses within the same vertical as it is in the real world. We do know that brands, products and the community present trigger points and that the goals of the user can change from recovery to discovery in the blink of an eye. We have the tools to test, measure and optimize this experience using flow targeting. I expect we’re closer than many believe to cracking this code and effectively targeting to the two intentions of users.