Answer this question, get featured on ShopCreatify

S

ShopCreatifyWe're writing an article about the process and challenges involved in transforming your online store into one that offers both B2B and DTC channels. And looking for insight from r/etailers, ecom merchants, manufacturers, or wholesalers, who have been through this journey. 1. Which transition did you make? Did you go from only DTC to also incorporating B2B or from B2B to DTC? 2. What were your biggest operational/UX challenges during the process? 3. Which parts of the transition were surprisingly straightforward? 4. Which CMS or platforms did you use to make the transition (Shopify? Woocommerce? BigCommerce?), and in what ways was it robust enough to handle both your channels? 5. Did creating a new digital revenue channel on your store improve sales overall? How so? Please no AI answers. We're after gritty on-the-ground experiences. Please, no SaaS or platform owners. Only merchants or the companies they used to build their online stores.

D

Destination CRMHello. I’m writing an article on a short deadline for Destination CRM (www.destinationcrm.com). I’m seeking to interview customer service managers, contact center experts, technology professionals, marketing and sales professionals, business faculty, companies, and other subject matter experts for the following story: Identifying the latest customer service/call center trends and technologies. Below is a list of questions I’m seeking answers to for this story. I can only conduct email interviews, whereby you or your suggested sources type up written responses to my questions below that I can use as quotes in my story (that’s also often easier and ensures no accidental misquoting). My deadline for written responses is noon central, Friday, March 6, 2026. Please let me know if you’d like to participate via written responses. Thanks! QUESTIONS 1. How is artificial intelligence fundamentally reshaping customer service and contact center workflows in 2026? 2. What are the most important technological and non-technological trends shaping customer service and contact center strategies this year, and why? 3. How has the definition of "excellent service" evolved since last year, and what do customers now expect as a baseline? 4. With routine tasks now fully automated, how has the "ideal candidate profile" and training for human agents changed? 5. Are traditional metrics like Average Handle Time (AHT) still relevant in 2026, or have new KPIs taken their place? 6. How are companies successfully transitioning their contact centers from "cost centers" into "revenue generators"? 7. What are the biggest hurdles in 2026 for maintaining a seamless "omnichannel" experience across emerging digital platforms? 8. In an era of high automation, how are brands successfully injecting "humanity" and brand personality back into the service journey? 9. How is the physical retail or office environment being integrated into the digital customer service workflow this year? 10. What specific strategies are being used in 2026 to protect customer privacy and data without adding friction to the user experience?Any other tips, thoughts, comments, or ideas on this topic you’d like to add? 11. What is your full name, title, company, and city/state headquarters?

S

SumatoSoftI’m collecting input for a report on AI readiness that will cover how companies move from AI pilots to production use (including GenAI) and the blocks to that transition. I’m looking for short, specific responses from business, operations, IT, data/ML, product, security, or functional leaders who’ve been directly involved in implementing AI. All contributors will be referenced and backlinked. Please include your industry and company size. What AI-powered tools do you have in production today? Please share (a) a workflow/function where AI is used day-to-day, and (b) the #1 factor that enabled AI implementation into production (e.g., data readiness, workflow redesign, product owner, MLOps/LLMOps, executive sponsorship). What was your biggest “AI readiness” gap, and how did you address it (data quality/access, integration with legacy systems, security/privacy, compliance, etc.)? What did you change, and can you share one metric that reflects the bottleneck or improvement? How do you measure value and manage risk once AI is deployed? Please name one value metric you track and one control you rely on. If relevant: what made you scale your AI or stop it?

This deadline has passed

View Similar Opportunities