Here’s a quick summary of some of the startups that will be featured at the conference:
Most visitors to a commerce site use the onsite search engine, yet many fail to find what they are looking for. And after just two failed searches, the majority abandon the site.
Constructor.io has set out to fix that, by providing an AI powered Search-as-a-Service solution. Machine Learning continuously learns from data such as customer behavior, product catalogs, product-related metadata, price changes and purchases. And it immediately applies those learnings to improve results ranking. With every search, every click and every purchase, customers provide info about what they want to buy. Constructor Search uses that valuable information to personalize and rank results.
This is combined with other technologies such as NLP to provide tolerance for fat finger typos and to infer intent from the search query. When users search for “butter”, they want to see salted butter or cream butter, not crunchy peanut butter in their results, for example.
And last but definitely not least, site owners can tune search optimization parameters to their business goals. Search results can be tuned to maximize revenue, conversions, loyalty, average order value or a combination of factors.
We all know that the tone of how someone says something conveys at least as much information as the actual words they say. Now OTO has created innovative technology to measure the emotion behind words and thus get a much better understanding of the intent.
These insights can be used, for example, to provide real-time coaching for customer agents right while they’re in the middle of a customer call. Because voice to text transcription isn’t required, the feedback can be much faster and more immediate. And managers can monitor calls in real-time for quality assurance and jump into the middle of calls that are trending downward.
Or the insights can be used to score customer service conversations for NPS or customer satisfaction without having to rely on surveying the customer since we know that customers seldom respond to post service surveys.
Another exciting use case is the ability to predict the nature of the conversation, based on previous reactions from similar customers. Early tests are showing that it might be possible within 1 – 2 minutes of a sales call to start predicting if the conversation will lead to a sale or not.
The big problem with online shopping is that it’s hard sometimes to get a good sense of a product before buying since you can’t touch or feel it. This makes shoppers hesitant to buy and also leads to returns if the product doesn’t turn out to be as expected.
ThreeKit solves this by providing a scalable way to embed realistic 3D images within the commerce platform that allows buyers to rotate, flip, scale and look at a product from all angles. And it’s not just off-the-shelf items that can be viewed this way. ThreeKit can show customers realistic 3D representations of products that don’t even exist yet. For a complex product, ThreeKit can break a product down into its various components and configuration options, and all those components can be mixed and matched. This approach allows for and scales to billions of possible combinations. And once a particular custom combination is chosen, the specs can be passed to manufacturing and the product then made to order.
The benefits to retailers are big. There can be up to a 40% increase in conversions and an 80% reduction in returns using this approach. Not to mention that customers who want to customize an item are often willing to pay a premium for that special, one-of-a-kind product.
The average enterprise uses 91 cloud marketing services (as of 2017) and in 2019, the marketing technology landscape is made up of over 7000 distinct solutions. These fragmented solutions represent a big problem for marketers when it comes to getting insights and analytics across all these different data silos.
Enter Adverity, which solves this problem by providing a LOT of pre-built data connectors to marketing data sources (200+ and climbing) that eliminate the need for manual data-wrangling. This fast-growing library of native connectors makes it easy to exploit every bit of data the source offers, without limitations on KPIs, dimension or metrics.
Adverity provides a best-practice data model across all sources out-of-the-box so marketers can slice, dice and customize their data according to their needs – without coding or maintenance.
And with the data all in one place, marketers can report on it using their favorite analysis tool, or use the analytics provided by Adverity.
No one likes waiting in a long checkout line at the store. Rapitag has pioneered a smart device that replaces antitheft security devices that the cashier needs to remove at checkout time with a smart device that customers, not cashiers, unlock and remove when they purchase the product with their mobile phone.
Using Bluetooth near-field communication, the user passes the phone next to the tagged item and can instantly get information on pricing and other product information for that exact item. Once the customer pays, using any common online payment option, a unique token is generated that unlocks the Rapitag device.
The device is more secure that either current mobile checkout technologies or older security devices because the Rapitag device is mapped to an individual product and is harder for shoplifters to manipulate.
The barrier of waiting in line is removed and the shopper can purchase instantly. That’s the e-commerce experience transported to the physical store!
Getting a handle on what millions of consumers think about your brand isn’t easy. Revuze uses AI to parse huge mountains of customer experience data – from commerce systems, call centers, social, emails and more – and turns all that unstructured text into explorable, actionable, business intelligence.
With “auto topic discover”, Revuze automatically discovers as many as 80 metrics for each product, then categorizes them and identifies trends. Brands have found insights that they might never have found any other way. For example, a leading razor manufacturer discovered that their brand reputation was going down and the reason for it was due to a shop selling fake products on Amazon, which, aside from the damage to the brand, was costing them $1.2M/month in lost revenue.
Brand managers can get a full inventory of KPIs and sentiment analysis for their brand, products and features. They can monitor competitors, and spot emerging trends quickly. And Revuze delivers their solution as subscription service without the need for a costly and time-consuming IT project.
These are just a few reasons why I’m excited to be heading to SAP CX Live. I hope to see you there!