惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

爱范儿
爱范儿
B
Blog RSS Feed
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
量子位
博客园 - 三生石上(FineUI控件)
博客园 - 【当耐特】
Attack and Defense Labs
Attack and Defense Labs
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
人人都是产品经理
人人都是产品经理
酷 壳 – CoolShell
酷 壳 – CoolShell
Apple Machine Learning Research
Apple Machine Learning Research
阮一峰的网络日志
阮一峰的网络日志
大猫的无限游戏
大猫的无限游戏
T
Tailwind CSS Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
罗磊的独立博客
V
Visual Studio Blog
博客园 - Franky
博客园 - 叶小钗
有赞技术团队
有赞技术团队
IT之家
IT之家
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
博客园_首页
J
Java Code Geeks
S
SegmentFault 最新的问题
Last Week in AI
Last Week in AI
月光博客
月光博客
博客园 - 司徒正美
小众软件
小众软件
The Cloudflare Blog
宝玉的分享
宝玉的分享
博客园 - 聂微东
WordPress大学
WordPress大学
雷峰网
雷峰网
V
V2EX
Engineering at Meta
Engineering at Meta
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
L
LangChain Blog
Jina AI
Jina AI
Hugging Face - Blog
Hugging Face - Blog
The Register - Security
The Register - Security
腾讯CDC
Microsoft Azure Blog
Microsoft Azure Blog
Recent Announcements
Recent Announcements
D
Docker
F
Fortinet All Blogs
美团技术团队
H
Help Net Security
U
Unit 42
MyScale Blog
MyScale Blog

Mastercard Dynamic Yield

Email, SMS and push done right: A marketing leader’s guide to channel selection How Valamar engages travelers earlier with real-time booking context Gartner Recognizes Mastercard Dynamic Yield as an 8‑Time Leader in Personalization Engines— Mastercard Dynamic Yield 2026 Personalization Maturity: Disruption Is Redefining E-Commerce Success Modern customer journey orchestration: Latest capabilities, best practices and omnichannel strategies — Mastercard Dynamic Yield Saks Fifth Avenue Elevated Luxury With AI Personalization 2025 Personalization Maturity Report for E-commerce - ES — Mastercard Dynamic Yield 2025 Personalization Maturity Report for E-commerce - PT — Mastercard Dynamic Yield How to Drive More Subscribers to Your Mailing List: Proven Strategies for MarketersMastercard Dynamic Yield Reconnect by Mastercard Dynamic Yield: Smarter Customer Journey Orchestration Send-Time Optimization — Mastercard Dynamic Yield Channel Prioritization — Mastercard Dynamic Yield Real-Time Adaptation and Dynamic Optimization — Mastercard Dynamic Yield Post-click Experiences — Mastercard Dynamic Yield Search Ranking Optimization — Mastercard Dynamic Yield Visual Search — Mastercard Dynamic Yield Semantic Search — Mastercard Dynamic Yield How Bergzeit Increased Conversions 3x with Conversational AI Email Deliverability Best Practices: Reach the Inbox. Deliver the Experience. The enterprise guide to IP warming: Boost deliverability, ensure compliance, and power seamless journeys Visual Search Meets Multimodal AI: A New Era of Product Discovery Where human ingenuity fits in the AI-driven marketing era Infographic: The state of personalization maturity in e-commerce - 2025 AI and Personalization Are Revolutionizing E-commerce Search Transform product discovery with Experience Search: AI that understands your shoppers AI Fuels New Demands for Personalization — Is E-Commerce Maturing Fast Enough? From Fragmentation to Connection: Mastering User Identification for Personalization — Mastercard Dynamic Yield 2026 Personalization Maturity Report for E-commerce - PDF — Mastercard Dynamic Yield Add To Cart Recommendation Modal — Mastercard Dynamic Yield Shoppable Video Notification — Mastercard Dynamic Yield Dynamic Yield by Mastercard Recognized as a Leader by Gartner® and Forrester Leroy Merlin Gains 32% Purchases with ML Recommendations Conversational Commerce: Your Guide to This Market-Shifting Technology Your Global Test Could Be Limiting Your Personalization Growth — Mastercard Dynamic Yield Personalize with Empathy to Meet Evolving Customer Needs The Resource Constraints Blocking Banks’ Personalization Gain Steering by Data: How to Avoid Assumptions and Motivate Your Team — Mastercard Dynamic Yield AI and personalization can close the empathy gap between brands and their customers A Leader in the Gartner Magic Quadrant for Personalization - Dynamic Yield Black Friday Is Coming—Is Your Personalization Strategy Airtight? Personalization Blueprint Survey - Dynamic Yield by Mastercard How Personalization Fuels Success in Latin America's Digital Boom Signet Jewelers Sees 88% Conversion Lift from Personalization Solving Data Issues for Financial Services with Personalization — Mastercard Dynamic Yield How to Executive Reporting Can Help You Grow Your Personalization Program Breaking the personalization barrier for banks Bring the personal back to shopping this holiday season​ with Shopping Muse Dynamic Yield makes Personalization a Breeze for Issuer Dynamic Yield by Mastercard Is Making Personalization a Breeze for Banks How to Deliver a Less Frustrating Online Shopping Experience VIDEO: Banking's Personalization Revolution: Data-Driven Transformation Bunnings' Buyer Center Casas Bahia's Buyer Center Magalu's Buyer Center Carrefour's Buyer Center 3 Tips to Integrate GenerativeAI into Your Personalization Workflow — Mastercard Dynamic Yield TUI Cruises Sees 10.3% Uplift in Add to Cart from Personalization The Revenue Gains From Personalization That FIs Can’t Ignore Calling All UK Banks: Personalisation Is Crucial to Meeting the New Consumer Duty Mandate What Marketers Miss in the GenAI Discussion vidaXL's Buyer Center The 2 Breakthrough Technologies Driving Smarter Product Recommendations Fashion Retailers: Your Product Feed Needs Spring Cleaning, Too — Mastercard Dynamic Yield Tommy Hilfiger's Buyer Center G-Star Raw's Buyer Center Hunkemöller's Buyer Center Here's Why Your Customers Are Tuning You Out Intersport's Buyer Center How AI Is Ushering in the Future of Interactive Commerce Mastering Channel Prioritization: How to Optimize Re-Engagement with a Winning Strategy Clark's Buyer Center Optimized messaging for purchase completion Affinity-powered triggered messages - personalization use cases Anticipate customer's next best item - personalization use cases Charlotte Tilbury's Buyer Center Rituals' Buyer Center The Dynamic Duo of A/B Testing and Personalization Müller's Buyer Center Next's Buyer Center La Redoute's Buyer Center Why Gen Z Craves Personalized Restaurant Experiences The human advantage in the age of AI and personalization Sky Personalizes Subscription Management for Millions On Leverages Personalization to Build Community Build-A-Bear Workshop's Buyer Center Oak Furnitureland's Buyer Center Coach's Buyer Center The Perfect Match: Marry Your CMS and Personalization Systems for Customer Love 4 Signs You Need to Move Beyond Your ESP's Email Personalization Functionality Sainsbury's, meet Dynamic Yield Charles Tyrwhitt's Buyer Center Burberry's Buyer Center Personalization in QSR: The Possibilities You Didn’t Know Existed The State of Personalization Maturity in Grocery/CPG Chanel's Buyer Center Swarovski's Buyer Center Building the Right It: How “Pretotyping” Guides Product Decisions with Concrete Data The Power of a Primary Audience Strategy for Financial Services Similarity Badge — Mastercard Dynamic Yield How Deep Learning is Adding Predictive Personalization Prowess to User Affinity Profiling
Turning mobile pain points into experiment design — Mastercard Dynamic Yield
2018-12-11 · via Mastercard Dynamic Yield

Summarize this articleHere’s what you need to know:

  • Mobile usage is skyrocketing, making it crucial for businesses to optimize the mobile experience to drive success.
  • Identifying and addressing customer pain points is key to optimizing the mobile experience. To do this effectively, a “pain point-first” approach is recommended.
  • This approach involves conducting in-depth customer research to understand their behaviors, motivations, and goals. This research lays the foundation for segmenting customers and identifying common pain points.
  • Once pain points are identified, they should be grouped into buckets for prioritization. This helps businesses focus their efforts on addressing the most impactful issues.
  • By understanding customer pain points, businesses can design targeted A/B tests and personalization strategies to address them. This can lead to measurable improvements in conversion rates and revenue.

A lot has changed in the past 10+ years in the A/B testing and personalization industry. That is true especially in mobile. Let’s focus on the tactical aspect of solving mobile customers’ pain points as key to your experimentation program’s success.

Mobile has gone from totally overlooked to “mobile-first” everything, and then “let’s kill two birds with one stone and go responsive” (my thoughts on that in a later blog post). But mobile is a grown adult now and it’s time for it to play a more prominent, if not a starring role, in your experience optimization and personalization program.

Statista.com data reveals mobile phone usage is on the rise. In 2018, 52.2% of all worldwide online traffic was generated through mobile phones, up from 50.3% in 2017. In addition, Google consumer insights research found that 89% of people are likely to recommend a brand after a positive brand experience on mobile, with 46% of respondents saying they would not purchase from a brand again if they had an interruptive mobile experience. To summarize the data: if you aren’t including mobile in your experimentation efforts, you’re losing customers and money.

I’m guessing you’ve read this far because you want to know the secret to extracting more out of your current experimentation efforts – more data, more insights, and perhaps most importantly, more wins. Now that I’ve revealed the headline, it’s time to get into the details.

Identifying mobile pain points

Aggregate client ROI data from surefoot.me reveals identifying customers’ mobile pain points and designing experiments to address them are critical to program success and customer happiness. This approach has led to measurable lifts in overall win rate and program success for our clients, and I’d like to share how it can do the same for you.

In order for you to understand our “pain point-first” experiment design methodology, I first need to explain that we begin every client engagement by conducting deep customer discovery research and identifying specific personas.

We go beyond the standard “male, age 35, median income”-style demographics and analyze a variety of different information including:

  • User tests
  • HotJar recordings
  • Customer service transcripts
  • Surveys
  • NPS scores
  • Google Analytics data

And more to gain a better understanding of customers’ behaviors, motivations, goals and problems. We’ve even talked to real, live people on the phone (?)!

Once we understand our clients’ customers on a deeper level, we break them down into various segments based on things like:

  • Device type
  • Regional location
  • Gender
  • Browsing behavior
  • Etc.

Turning pain into purpose

We’ll then shift our focus to identifying segment-specific pain points. Often, themes emerge as customers struggle with the same things, so we group those themes into “buckets” for easier test prioritization. For example, if we’re observing customers struggling with a checkout form validation, we might group them into a “Form UX” bucket.

When the pain point discovery process is complete, we step back and assess our “pain buckets.” The most common pain points reveal themselves and it’s usually quite obvious what we need to tackle first via experimentation. As an added bonus, this process can make test prioritization less painful (har har) by replacing emotional, opinion/HiPPO-based prioritization with data.

I’ve been told that pictures are worth a thousand words, so below are a few low-fidelity mockup examples that illustrate mobile pain points we’ve identified and how we solved them through experimentation:

Use case 1: product on the mobile homepage

Pain point: Through a combination of Google Analytics and HotJar data, we observed that mobile homepage visitors who didn’t use the hamburger nav to begin shopping weren’t engaging with homepage content and were more likely to exit the site.

Solution: Products were added to the mobile homepage, directly beneath the homepage hero section, to establish visual confirmation and trust that visitors were on the right site and enable them to begin shopping faster.

Results: 3% lift in visits to PDPs, 5% lift in AOV, 2.2% lift in revenue, all at 95% statistical significance.

Use case 2: frequently bought carousel with quickshop

Pain point: Through a combination of HotJar recordings, client data and user interviews, we learned that mobile visitors were using the cart as a “comparison tool” to view, add and edit their product selections (aside: this is something we’ve seen across clients and is well-documented in UX research). As part of this workflow, visitors often went backwards through the conversion funnel to continue shopping, which posed risks to the end transaction and negatively impacted revenue and average order value (AOV).

Solution: Added Dynamic Yield’s “frequently bought together” recommendations widget at cart and, as an added bonus, created “quickshop” functionality so visitors could add additional products to cart without having to go back through the conversion funnel.

Results: 2.5% lift in cart adds, 3.4% lift in AOV at 95% statistical significance.

Use case 3: streamlined mobile cart

Pain point: Through a combination of HotJar recordings and user testing, we identified that many mobile cart visitors were overwhelmed by multiple call to actions (CTA)’s competing for their attention. The biggest offender was the “Continue Shopping” button, which visitors overwhelmingly mistook for a “Continue to Checkout” button, as their default behavior was to tap the first large button they saw. Many were extremely confused when they were taken back to shop, wondering if the site was broken and also revealing that they didn’t read the CTA and had no idea what they tapped.

Solution: Streamlined the cart design by eliminating competing CTA’s and made the checkout button the boldest, primary CTA.

Results: 3.1% uplift in checkout visits, 3.5% conversion lift, 4.5% revenue lift, all at 95% statistical significance.

Customer-first = mobile-first

If you want to derive maximum value from your experimentation program, I encourage you to start by reconnecting with your customers and gaining an understanding of their pain points. Especially on mobile devices, where brands typically see more traffic but experience barriers to conversion.

Once you more fully understand your customers’ problems, you can begin solving them through thoughtful experiment design via personalization and experimentation solutions like Dynamic Yield that enable marketers to deliver highly targeted experiences.

So what are you waiting for? Stop reading and go talk to your customers!