In this episode of Partner Connect I show the latest enhancements CoreMedia has implemented with a few Watson API’s. I show three cool integrations in this video: Watson Conversation Services, Watson Visual Recognition Services, and Watson Translation Services.
You have heard of “chat bots”, well, think of Watson Conversation as a chatbot on steroids. CoreMedia has done some really slick dialog in their studio to help users complete various tasks within their software. They then use Watson Visual Recognition to automatically suggest tags and even recommend if products were found in the image – which you can then create image maps and link them into your commerce catalog. Lastly, once your landing page or content is created you can then localize your content with a click of a button using Watson Translation services!
Since this video is so long I do a 3 minute overview in the beginning because the actual demonstration is about 15 minutes but well worth it!
Retailers have five common business problems executing across multiple channels and their brick and mortar stores:
- Personalization across all channels leveraging company data
- Common user experience from unstructured content
- Full circle learning / input reintroduction
- Connected commerce and digital experience
- Online / in-store inventory execution & Supply Chain Management
In this video I tell a story about the Aurora company and walk through their new summer Albini dress campaign. The Aurora team uses the Watson Customer Engagement platform to drive a successful campaign. The story centers around Katie, an avid Aurora shopper, where the Aurora team has visibility into activity across all channels and drives customers into their brick and mortar stores to drive additional sales.
Watch how the Aurora team uses the Watson Customer Engagement platform to execute an email campaign and learn about their shoppers across their web site, mobile application, call center, and stores.
Working with REST services can be extremely error prone. You could have latency, network failures, or at worse case even total down time. I have been writing a lot of code as of late that requires extreme error handling and graceful failing when dealing with remote REST services and in general web calls – like parsing or loading external web sites for DOM evaluation as an example. The issue is you can’t trust the performance or even trust the service is even available and knowing what methods are failing or causing the bottlenecks could be extremely cumbersome. You could implement network profilers to capture what is going on, or, you could implement a CircuitBreaker design pattern and take control of your calls yourself.
Welcome the Circuit Breaker design pattern. This pattern allows you to monitor a specific function call and “break” gracefully if it has taken too long or even fails. This is usually symptomatic with asynchronous calls that may require calling other code on completion, fail, or timeout. Methods like jQueries ajax where you supply the various error, complete, and done methods work great and even languages like Swift and Java have similar callbacks but it lacks data around the calls. The CircuitBreaker design pattern will make your code easier to follow for race conditions and it can even track statistics around the calls…
If you are a Swift programmer you can check out the Swift CircuitBreaker project on GitHub. It has complete documentation and makes using this design pattern very easy and straightforward.
Now, what sets this package apart in my opinion is it also gives a large set of statistics around the calls. Capturing how long calls take (latency), how many successes, failures, and even average response times. From an SLA perspective this is great! You can then quickly identify what remote calls to “other” services are the primary bottlenecks or problems in your application.
We have several offerings spanning Marketing and Commerce and many more coming this year. As a developer, you can now sign up to be notified when products and API’s become available on the IBM marketplace. Bookmark it and sign up today for notifications.
Check it out today.
This is good news for IBM and while Gartner mentions Watson Commerce Insights for predictive merchandising and predictive search, I am not sure why it doesn’t include products like Dynamic Pricing – which is clearly stated as a primary initiative for most B2B sites by 2018. Analytic’s and augmented intelligence is a big area IBM is investing in and it ties closely with managing customers for both B2C and B2B sites. As stated in this report, by 2020, smart personalization engines used to recognize customer intent will enable digital businesses to increase their profits by up to 15%. I don’t think products like IBM Predictive Customer Intelligence or Watson Customer Experience Analytics are well represented in this report and by next year there will be even more augmented intelligence features in the IBM suite. At some point, the Digital Commerce quadrant has to recognize these add-ons as a base part of doing business in this report and this year they should have clearly been listed as strengths in the industry.
Another area I think the report falls short on is order optimization. With more and more companies moving to buy on-line pick up in store or more specifically buy on-line ship from store, you are going to see more demand for order fulfillment optimization, something Watson Order Optimizer covers very well.
Some key messages from the report IBM is focusing on:
- IBM is a Leader, based on its product functionality, ability to support B2C and B2B business models, and its supporting ecosystem of applications that connect to its commerce platform across the globe.
- IBM maintains an extensive set of partners in the digital commerce ecosystem, which was highly thought of by its reference customers — all scored it “very high” or “outstanding.”
- By 2018, 40% of B2B digital commerce sites will use price optimization algorithms and configure, price and quote tools to dynamically calculate and deliver product pricing.
- By 2020, 25% of leading online sellers will have enabled first-generation “commerce that comes to you” capabilities.
- By 2020, smart personalization engines used to recognize customer intent will enable digital businesses to increase their profits by up to 15%.