Recommendations Reboot: Improving RIO with Experimentation
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Recommendations are table stakes for modern organizations, but by now it’s no secret that the effort required to both manually select recommended products and experiment with styles and layouts is preventing retailers from maximizing potential revenue. In this \ session learn how leading retailer, Stella & Dot, is applying an experimentation mindset to their recommendations strategy and the benefits they have reaped thus far. Also, get a sneak peek at how Optimizely is implementing recommended content for its blog and Knowledge Base.
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Autotrader's Product and Engineering teams were ahead of the curve many years ago when they built a home-grown solution for leveraging feature flags to support server-side testing. Over the years, the industry eventually caught up and surpassed this proprietary tooling and the team had a choice to make: Re-invest into the local solution or completely retool. In this case study, Scott Povlot, Principal Technical Architect, and Seth Stuck, Director of R&D Analytics, will discuss their journey in selecting and then migrating to their next generation of experimentation tooling. They will discuss selection criteria, pros and cons, and outline how they were able to make the migration to Optimizely successful and lessons learned along the way.
Zillow + Optimizely: Building the Bridge to $20 Billion Revenue
Join Jason Tabert, Senior CRO Marketing Specialist, and learn how Zillow is using Optimizely’s experimentation, personalization and integrations to help grow their revenue to $20 billion by helping their customers cross the real estate chasm from despair to delight.
The Future of Optimizely for Technical Teams
Optimizely has been reimagining the future of progressive delivery and experimentation, improving every part of the platform to empower technical teams to build, ship, and iterate faster. Learn about the latest enhancements to Optimizely Full Stack and the Optimizely Data Platform, and get a sneak peek at the upcoming roadmap.
Empowering Agents to Provide Service from Anywhere: Contact Centers in the Ti...
The coronavirus pandemic has pushed contact center leaders to accelerate technology adoption and empower their teams to work remotely. Join this session with State Farm, Salesforce, and Optimizely to learn how contact centers can adapt quickly and successfully in the time of COVID.
Experimentation Everywhere: Create Exceptional Online Shopping Experiences an...
Our new normal has accelerated eCommerce trends by 4-6 years. The Optimizely team shares how experimentation can help retailers fast forward their online sales strategy with Microsoft Dynamics 365 Commerce.
Building an Experiment Pipeline for GitHub’s New Free Team Offering
In April 2020, GitHub announced a new Free for Teams plan. Behind the scenes, the engineering team was also setting up an experiment pipeline and an integration with Optimizely. In this session, we will take a peek at the process of setting up the integration, learning about the behavior of this new Free for Teams customer segment, and the next steps for this experiment pipeline.
AMC Networks Experiments Faster on the Server Side
Speeding up innovation only matters if it helps you drive positive outcomes. At AMC, experimentation enables the product and platform teams to challenge their assumptions, maximize impact, and evaluate ideas as painted door tests before investing in significant development. A commitment to test everything across 9 platforms fueled their search for the most scalable solution.
In this session, you'll learn how to:
Leverage server-side testing to experiment quickly
Scale across web, mobile, and OTT applications
Determine when client-side testing is more efficient
Evolving Experimentation from CRO to Product Development
An obsession with data, efficiency, and delivering incredible customer experiences are just a few things that the CNN Consumer Science and Software Engineering teams have in common. Simple A/B testing practices evolved into a culture of experimentation, sparking new development practices across the organization. Learn how they drive results across their entire platform from websites to mobile apps.
Overcoming the Challenges of Experimentation on a Service Oriented Architecture
Growing from an early stage startup to a national leader in financial literacy is no small feat, and there are a ton of lessons that we have learned at Greenlight as we have grown. Long gone are the days where we would ship something and cross our fingers hoping that it makes some kind of impact on our customers. Now we’re in a world where we can learn ahead of time how much impact a feature will have on the business, before we even launch! In today’s conversation, we’ll discuss how we use Optimizely’s feature flags in our microservice architecture using Optimizely Agent while keeping user IDs and context synchronized.
This session will cover:
How we set up Optimizely Agent and use it in a kubernetes deployment
How we created a user-aliasing service
How we access Optimizely both on the frontend and in the backend services.
How to build a full stack feature
How to manage the rollout using Optimizely’s feature flags
How The Zebra Utilized Feature Experiments To Increase Carrier Card Engagemen...
A/B testing is an essential element in any product managers playbook. However having the freedom and flexibility to customize testing based on what the data is saying often requires a lot of time and effort, particularly when it comes to engineering resources. Optimizely offers a flexible approach to experimentation through the use of feature testing, which provides more customization options without the additional development effort typically required to implement these feature optimizations. Megan Bubley, a Senior Product Manager at The Zebra, will share her experience working with Optimizely’s feature tests to create a results page where users can compare multiple auto insurance options driven by actual user needs, as well as her experience customizing the experience based on device platform.
Making Your Hypothesis Work Harder to Inform Future Product Strategy
At Treatwell, each experiment goes beyond improving a single business metric. Experimentation works to evolve their product while enriching customer insights in order to deliver the best digital experience to their users. Join Laura Howard, Lead Product Manager, and Dennis Meisner, Senior Product Analyst, to learn their secret to making their hypothesis work harder and how getting their hypothesis right has improved Treatwell’s funnel progression and order health, as well as helped them make critical decisions on their product experience.
Kick Your Assumptions: How Scholl's Test-Everything Culture Drives Revenue
Amy Vetter, Consumer Experience Manager, Direct To Consumer, Europe, will walk you through some of the tests that she and her team run across the Scholl brand. Amy will highlight surprise learnings and how to remove the fear of failing. The team is empowered to test everything possible that will allow the customer to get the best experience and also support the brand’s goal for more revenue and customer data.
Experimentation through Clients' Eyes
At Charles Schwab, they have a mantra of viewing the world through their client’s eyes. When it comes to building digital experiences and running experiments, winning isn’t just about moving metrics, it’s also about improving customer experience. Sara Tresch, SVP of Digital Services at Schwab will be discussing how Schwab designs products and experiments with a client-first mindset.
Shipping to Learn and Accelerate Growth with GitHub
Will 2020 mark the shift to a remote-first world in the long run? For GitHub, a distributed workforce is nothing new. Join Sha Ma, VP of Engineering, and Gregory Ceccarelli, Director of Data Science, to learn how they built and scaled a successful experimentation program. They'll share their experience implementing Optimizely across timezones, a remote workforce, and a new business model.
In this session, you'll learn how to:
Optimize UX for a freemium business model
Use data to deliver customer-centered products
Scale experimentation and accelerate growth
Test Everything: TrustRadius Delivers Customer Value with Experimentation
When done right, experimentation can help you validate the product you’re building and create winning customer experiences. And it doesn’t take a big engineering team to make this happen.
TrustRadius, the most trusted review site for business technology, uses experimentation to build an online community through website and server-side experimentation. The small but mighty TrustRadius team runs experiments throughout the buyer’s journey to engage different user personas and understand outcomes in real-time.
Watch the webinar recording featuring Rilo Stark, product manager at TrustRadius, and Jack Peden, senior software engineer, to understand their data-driven experimentation strategy and how TrustRadius uses Optimizely Web and Full Stack products to tailor experiences to different customer segments and mitigate risk through A/B/N and painted door tests.
Optimizely Agent: Scaling Resilient Feature Delivery
In this session, you will learn: how to embed feature flagging sitewide to deliver safer, faster releases, best practices for implementing feature flags in a services-oriented architecture, and the latest enhancements you need to help your team recover faster when ship happens.
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Clover Rings Up Digital Growth to Drive Experimentation
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Make Every Touchpoint Count: How to Drive Revenue in an Increasingly Online W...
Make Every Touchpoint Count: How to Drive Revenue in an Increasingly Online W...
Atlassian's Mystique CLI, Minimizing the Experiment Development Cycle
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Zillow + Optimizely: Building the Bridge to $20 Billion Revenue
Zillow + Optimizely: Building the Bridge to $20 Billion Revenue
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Building an Experiment Pipeline for GitHub’s New Free Team Offering
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Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
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Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
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The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
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Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
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HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
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- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
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Recommendations Reboot: Improving RIO with Experimentation
- 1. Recommendations Reboot Improving ROI with Experimentation Opticon Virtual Summit Product Manager, Data Optimization Stella & Dot Ankit Raheja Jon Noronha Director, Product Management Optimizely
- 4. What were the benefits and challenges of manual recommendations?
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- 14. Parting thoughts
- 15. Thank you!