In a Q&A with TechRepublic, Reflektion's Sean Moran says that real-time analytics will help optimize customer experiences and will deliver on clients' needs for deep insights.
In an email Q&A with TechRepublic, Moran stated that predictive analytics is reaching its next evolution where solutions will deliver incredible insights. Two other trends he sees in the space include greater use of recipes, or machine-learning algorithms, and real-time optimization of customer experiences.
Sean Moran joined the firm in 2013 as CEO, coming from a sales and business development role at Monsoon Commerce. In our interview he shared that Reflektion's approach to customer personalization and the quality of the technology team attracted him to the post.
TechRepublic: What trends in predictive analytics do you see over the next two to three years?
Sean Moran: We see three big trends happening over the next few years. The first trend is a broader use of recipes, or blends of machine-learning algorithms, being applied to deliver successful results. It's no longer "which algorithm is most successful?" as it is "what is the right blend of machine learning applied to individual challenges that will provide more programmatically successful answers?".
The second trend is the increased use of predictive analytics applied automatically, in real time, to create optimized customer experiences. This will make sure that we are profiting from the wealth of data instead of spending too much time in post-event analytics.
Lastly, we see a much faster adoption of predictive analytics in everything imaginable. We have gone through this era of capturing every data point, but have remained relatively stagnant with what we have done with the data. Now, we are entering the next evolution where we will apply predictive analytics to capture incredible insights. The success stories will range from the mundane, but helpful, to the incredible and life changing. We are starting to exit the hype era and are entering the implementation age.
TechRepublic: What is the value proposition for Reflektion?
Sean Moran: Reflektion provides retailers and brands with a platform that creates a highly intuitive and personalized shopping experience for their customers. By capturing and analyzing every unique customer behavioral touch point and applying machine learning algorithms, we are able to deliver "true" personalization that increases customer engagement, customer conversion rates, AOV (Average Value Order), and return traffic. As a result of implementing this highly personalized shopping solution, clients like Converse, O'Neill, and Metal Mulisha have achieved sustainable revenue lift of between 13% to 46%.
TechRepublic: What convinced you to join Reflektion as CEO? How do you see your mission at the firm?
Sean Moran: There were two things that convinced me. The first was Reflektion's approach to the concept of personalization at the granular, individual customer level. I've been in and around the retail industry for many years, and I feel that technology providers haven't delivered on the concept of personalization yet. Our approach is unlocking that opportunity so a customer's engagement with a brand can be more intelligent and intuitive and meet the expectations of the new digital consumer.
The second element that convinced me to join Reflektion was the power and pedigree of the technology team. We have some of the brightest engineering minds applying contemporary technologies to the challenge of personalization and are really cracking the code. Our technology team thinks in completely new ways and is applying new approaches that are incredibly refreshing and successful.
TechRepublic: What differentiates your firm's technology and solutions?
Sean Moran: Reflektion is in the unique position to create a true "market of one" for our clients. Our platform analyzes what each visitor shares with us through their online store interactions, and we actively apply predictive analytics towards an experience that's more conducive to finding what the visitor will like and increasing the likelihood of purchase.
By applying machine learning algorithms to the wealth of first party shopping data stored in our Customer Intelligence Engine, we create a more complete experience that identifies a potential buyer's preferred products, personalizes the landing pages they see, brings individual relevancy to their search results, and makes for more efficient interactions on mobile.
Finally, our continual learning platform ensures that every engagement a customer shares with our retailers results in a better, more profitable experience for both. We're not just discovering data; we're actively providing improvements that translate into significant ROI.
TechRepublic: How can clients use your solutions to gain customer insights?
Sean Moran: Since Reflektion captures every element of an individual's shopping behavior in our Customer Intelligence Engine and overlays our recipe of machine-learning algorithms, we're able to provide a completely new level of insight for our clients. We are correlating data with preferences and creating the roadmap to personalization.
Based on this wealth of data, we can surface nuanced insights into shopping behavior for groups and products. We identify fast moving trends and anomalies, and once discovered, immediately alert our clients of opportunities. We also leverage this same engine to automatically identify customer segments that our clients have yet to uncover. These insights aren't based on hunches, or last year's customer data, they are based on real-time data that keeps our clients looking forward, rather than gazing in their data's rear-view mirror.
The Reflektion Customer Intelligence Engine is the brains of our platform. It provides unparalleled views of data. At the heart of our engine is the predictive analytics overlay to all this data. It is used to make intelligent presentations in real-time to customers on our clients' websites and as a complete overlay to smart segments. Many of the insights we capture are automatically turned into actions on the website so the insights can be put to work creating that unique, personalized experience.
TechRepublic: Would you share a customer success story?
Sean Moran: Although O'Neill Clothing is now a global beach lifestyle brand, it has never forgotten its small-store roots. The company's goal is still the same: treat each customer — whether visiting online or a brick-and-mortar retail outlet — as a unique individual by well-trained staff that caters to their needs with tailored product assortments. To duplicate the store experience online and offer each visitor an individualized product assortment that takes into account everything from the shopper's unique style to the weather and surf conditions in their region, O'Neill needed to find a way to tailor the online experience. To that end, O'Neill partnered with Reflektion to help them detect trends and predict in real-time what each customer is most likely to buy next online.
Empowered with Reflektion's patented algorithms and machine-learning technology that tailors a shopper's experience down to a minute level, O'Neill customers benefited from the same personal shopper experience as those who shopped in-store. By using data from each customer's previous interactions and combining it with trending product and hot selling item data, along with demographic data such as customer location, age and prior purchases, individual real-time recommendations were presented to the consumer as they shopped.
Our innovative and insightful search functionality enabled O'Neill to instantly personalize the online shopping experience by promoting specific products tailored to their unique customer profile as they typed in their search inquiry. Due to the individualized personalization on their website, O'Neill saw an immediate uptick in revenue per visit, 26% increase in conversion rate, 17% increase in average order size and 85% increase in engagement. O'Neill continues to enjoy continual growth in revenue per visit, larger average order size and increased customer engagement, all of which map back to Reflektion. [Watch a video of the O'Neill case study with Reflektion.]