Customer Experience

Pay attention! We’re delaying a week for those of you who may be on Spring break and/or celebrating the holiday. Ok, no pancakes, but waffles-a-plenty. Join the local UX and Digital Design community for a casual monthly breakfast. Look for us upstairs!

Let’s try this popular Italian restaurant in Reynoldsburg. This is the menu: https://scaliristorante.com/#4e468054-0235-43e2-81c2-44e061341e9e

**The Data-Driven Brand: Using Analytics to Shape Perception** Can you use analytics to improve tacos? This being CBUSDAW, we think the answer is probably “yes”, but we’re not sure how to implement or test this theory. For our April meetup we’ve got Sara Kear, CMO of Condado Tacos, to investigate this delicious question. Sara will explore how she blends quantitative data and qualitative customer feedback to shape brand positioning and drive business decisions. We all know that marketing and analytics go way beyond attribution. Sara will show how Condado uses customer insights to inform product and pricing strategy. She’ll also highlight how Condado leverages customer feedback at scale to influence operational priorities, positioning marketing as the voice of the customer across the organization. In the last 12 years Condado has gone from one location in Columbus to 52 locations across 10 states, so we’re guessing there’s more to that growth than really good guac (though the guac probably helps). Ultimately, this talk focuses on the intersection of art and science—using data to inform creativity and build a brand that resonates with customers in a measurable way. **About Our Speaker** Sara Kear is Chief Marketing Officer at Condado Tacos, where she oversees brand, restaurant design, menu and pricing strategy, off-premise including catering, and customer data strategy. Since joining in 2021, she has helped grow the brand from 19 to 52 locations while building a data-driven marketing organization focused on loyalty and customer insights. Condado has since been named to the Inc. 5000, recognized as Breakout Retailer by Chain Store Age, and consistently ranked among FastCasual’s Top 100 Movers & Shakers. Thanks to our 2026 sponsors: [Clarivoy](https://www.clarivoy.com), [What Box Consulting Group](https://www.whatboxconsultinggroup.com), [Conductrics](https://www.conductrics.com), and [Piwik PRO](https://piwik.pro) More info at [cbusdaw.com](https://cbusdaw.com)

Join us for our April Book Club gathering where we will come together to discuss *[Stop Me if You've Heard This One](https://www.kristenarnettwriter.com/stopmeifyouveheardthisone)* by [Kristen Arnett](https://www.kristenarnettwriter.com/about) in a safe and welcoming environment. Make new friends who share your passion for books and connect with fellow LGBTQ book enthusiasts.

**Welcome to the Women’s Columbus Bogleheads® Sub-Group** This sub-group is for **women who want to learn and discuss finances in a safe, supportive space**. For those interested in moving towards financial independence and retirement by learning investment basics, choosing your 401(k) investments, minimizing taxes, and more. We’re a local chapter of **Bogleheads®**, following a long-term, practical investment philosophy: [Investment Philosophy](https://www.bogleheads.org/wiki/Bogleheads%C2%AE_investment_philosophy): https://www.bogleheads.org/wiki/Bogleheads%C2%AE_investment_philosophy [Bogleheads Forum](https://www.bogleheads.org/index.php): https://www.bogleheads.org/index.php No question is too small, and no experience is too simple. Share, ask, and learn — at your own pace, without judgment, in a group of like-minded women. Let’s build confidence and knowledge **together**!

The Fellowship of the Star Schema: Transforming OLTP Data for Power BI One does not simply build reports on OLTP data. Join us on an epic journey from the depths of raw, normalized tables to the shining halls of a well-modeled star schema fit for Power BI greatness. We will demystify the differences between OLTP and OLAP, walk through star schema vs snowflake (and why Power BI has a clear favorite), and show you the compression differences between normalized and columnar storage that will make you never look at an OLTP model the same way again. We will cover the different types of dimensions, when to use them, and how to handle Slowly Changing Dimensions without losing your mind. You will leave knowing exactly how to identify a bad model, how to convert OLTP data into a clean star schema, and how to forge relationships that rule them all. Whether you are a data wizard, a curious hobbit, or somewhere in between, your models will never be the same.