







Practical guides on loyalty programs, retention strategy, UGC, and emerging trends like agentic commerce. By the team behind Zinrelo + TINT.
LoyalFans Advice (/c/LoyalFansAdvice) - OddsRabbit
Tips, advice and support for creators on LoyalFans.

AIDA model | Marketing | Research Starters | EBSCO Research
<p>The AIDA model is a marketing framework that outlines the stages consumers typically go through when making a purchasing decision: Attention, Interest, Desire, and Action. Developed in the late 19th century by American marketer Elias St. Elmo Lewis and later refined by Edward Strong in the 1920s, this model aims to guide marketers in capturing potential buyers' attention and leading them toward a purchase. </p> <p>In the Attention stage, marketers employ engaging strategies to attract consumers, often using eye-catching visuals or intriguing information. Next, the Interest stage focuses on maintaining that attention through memorable content or relatable messaging. The Desire stage demonstrates how a product or service fulfills the consumer's needs, often using persuasive techniques like testimonials or demonstrations. Finally, the Action stage prompts the consumer to make a purchase, providing clear instructions on how to proceed.</p> <p>While the AIDA model remains relevant, marketers today may adapt it to incorporate new elements, such as Retention or Satisfaction, reflecting the evolving digital landscape and consumer behavior. Overall, the AIDA model serves as a foundational tool for understanding consumer engagement and facilitating effective marketing strategies.</p>

Customer Engagement Platform for Email, Push Notifications, & SMS
The world's leader for mobile push notifications, web push, SMS, email and in-app messaging. Trusted by 2 million+ businesses to send 12 billion+ messages per…
A guide to the anatomy of effective commerce agents | Claude by Anthropic
The architecture, latency & cost techniques, and eval practices for agents that make it easier to buy and sell online.

The Fourth Theory of Agent Trust: Emergence - Astral's Blog
Signals: Toward a Self-Improving Agent | Factory.ai
Traditional product analytics tell you what happened. Session duration, tool calls executed, completion rates. But they...
I used Open Source Apps for 90 days. Here are my favorites
User Onboarding: The complete guide to activating and retaining users
Learn what user onboarding is, why it matters, and how to design flows that activate and retain users with best practices, examples, and tools.
Are Self‐Service Customers Satisfied or Stuck?
This paper investigates the impact of self‐service technology (SST) usage on customer satisfaction and retention. Specifically, we disentangle the distinct effects of satisfaction and switching costs as drivers of retention among self‐service customers. Our empirical analysis examines 26,924 multi‐channel customers of a nationwide retail bank. We track each customer's channel usage, overall satisfaction, and retention over a 1‐year period. We find that, relative to face‐to‐face service, customers who use self‐service channels for a greater proportion of their transactions are either no more satisfied, or less satisfied with the service they receive, depending on the channel. However, we also find that these same customers are predictably less likely to defect to a competitor if they are heavily reliant on self‐service channels characterized by high switching costs. Through a mediation model, we demonstrate that, when self‐service usage promotes retention, it does so in a way that is consistent with switching costs. As a robustness check, we examine the behavior of channel enthusiasts, who concentrate transactions among specific channels. Relative to more diversified customers, we find that self‐service enthusiasts in low switching cost channels defect with greater frequency, while self‐service enthusiasts in high switching cost channels are retained with greater frequency.

🚨Our new research examines agentic shopping: can you consistently predict (or, using marketing, influence) what an agent chooses? Nope. We found that even small differences (viewing order of pages, memories) changed AI preferences in unpredictable ways. papers.ssrn.com/sol3/papers.cfm?abstract_id=7…
Just got off a great call with @kandake.africa around "Log in with [Your atproto term here]" My closing keywords for how I think we need to approach this web-scale consumer infrastructure project: Trust - Reliability - Legibility Toto, I don't think we're in microblogging anymore.