Consumers are spending more and more of their time on mobile devices instead of their desktop. While this has been a boon for marketers looking to reach customers through social media, email, QR codes and location based marketing, it’s had an overall detrimental effect on mobile e-commerce.
What is the problem with mobile? While most major retailers offer an app, the apps were basically an adapted version of the website. For distracted users with a small screen and no keyboard, this setup simply doesn't work. The consumer wants to find products relevant to them quickly without dealing with awkward links or search bars
In other words, in order for an app to be effective, the content has to be different. Startups like BloomReach and major retailers like Walmart are already working on adapting mobile. How? By applying big data through reflected intelligence.
What is Reflected Intelligence?
For those still trying to grasp the concept of big data, reflected intelligence may just sound like another hype word. However, reflected intelligence is exactly what many marketers and business leaders have been looking for: a practical application of big data that has been made available by technologies like Apache Hadoop.
So here’s the rundown: Search has come a long way since it was first used for internal catalogs. Essentially it has evolved from simple text retrieval to providing relevancy rankings across millions of data stores. We’re all familiar with this. We type a few words into Google, and the most relevant sites pop up almost instantaneously.
Reflected intelligence takes this process one step further by combining search with big data. Big data is able to capture consumer behavior online: what they search for, what they click on and what they are talking about on social media. As businesses access and act on this data, they enter a cycle with the consumer and the search engine, as shown in the figure, that over time creates more relevant searches for the individual consumer and provides even more data to the company that it can use to cater landing pages, searches and mobile apps directly to the consumer.
What Can Be Done with this Process
So, how can businesses use reflected intelligence to their advantage, specifically in improving the effectiveness of mobile apps for e-commerce? The possibilities are almost endless, but here’s a look at five to give you an idea.
1. Mobile-Specific Design
The first thing reflective intelligence does is allow for a mobile-specific design. In order to quickly provide relevant content, a company has to be able to know what is relevant to each consumer. Reflective intelligence allows this by giving insights into the consumer’s gender, age, previous searches and even pins on Pinterest.
Imagine being able to program your app to have that same pair of shoes that a consumer pinned on Pinterest show up at the top of the app’s landing page complete with a recommended outfit to go with it. That is effective mobile design.
2. Predictive Search
Everyone hates typing on their smartphone. Having an effective predictive search can go a long way to quelling consumer frustration and getting them to the product they want faster, so they can make a purchase. BloomReach created a predictive search for its mobile clients that analyzes the client’s app and site plus millions of websites and billions of consumer interactions to predict what consumers are looking for when they type in just a letter or two. The predictive search pulls up a list of options to click on, so the consumer can forget about typing all together.
3. Product Recommendations Specific to Consumers’ Interests
Specific product recommendations naturally follow greater consumer insights. Some retailers, like Walmart that have customers return week after week for the same products, could start to generate suggested shopping lists on their app based off of what the customer regularly buys, and products they may have been searching for or looking at. Browsing on mobile apps can also be improved by providing a “more products like this” button that allows consumers to easily find products similar to the one they are looking at.
4. Customer Recognition Across Platforms
Right now, unless a customer is logged in to a webpage, the page won’t recognize a consumer when he or she moves from desktop, to tablet, to mobile. However, reflective intelligence makes recognizing a particular consumer’s “profile” possible by keeping track of similar searches and Internet networks. By recognizing this, a mobile app would be able to recommend a certain product right away based off of what the consumer was looking at on their desktop as if the consumer had never left the page.
5. In-Store Enhancement
Intelligent apps can be useful in-store as well. Walmart, for example, is programming its app to sense when a customer is in a Walmart store and prompts the customer to switch the app to “store mode.” The app can then scan items for prices and discounts or provide on demand information, such as which shoes are the most popular in a particular price range.
Reflected intelligence has the potential to significantly improve mobile apps, specifically in improving revenue in e-commerce, but it has its challenges. Consumers will notice that an app is accessing and using their online behavior, which naturally leads to privacy concerns.
While it’s up to the individual organization to ensure the safety of their customer’s private information, companies can help to quell customers’ concerns by explaining that the data being collected is basically an “Internet behavior” profile that isn’t even connected to their name. In the end, consumers will quickly adjust as they start to appreciate the improved mobile experience.
Title image courtesy of Sergey Nivens (Shutterstock)
Editor's Note: Want more tips from this month's focus on the mobile digital experience? Read Harry Blodgett's Think Beyond Responsive Design to the Responsive Experience