How to make sure you set the right prices in the area of AI agents and social media?
This seminar explores how retailers can modernise pricing in a world shaped by AI agents, social media and rapidly shifting customer behaviour. You’ll see how data, forecasting, experimentation and elasticity‑driven pricing can improve margin, markdown performance, and decision quality, with real‑world retail examples and measurable results.
This session will explore how retailers can use Databricks to implement advanced pricing strategies. Topics include:
- Using causal inference to measure promotion impact
- Markdown optimisation strategies
- Building scalable pricing models on Databricks
- Operationalizing pricing analytics across retail organizations The webinar will demonstrate how retailers can move from descriptive analytics to decision intelligence.
Is this webinar for you?
Platform and data leaders
Data platform owners, heads of data & analytics, CDOs, data engineers, data scientists, and pricing systems or analytics product owners who want to understand what modern, data‑driven pricing actually requires from their platform and models.
What you will take away:
- A clear view of how modern pricing, experimentation, and elasticity‑based methods translate into concrete data and platform requirements.
- Practical examples of how Databricks can support scalable pricing models, ML‑based demand forecasting, and promotion impact measurement.
- Real‑world case studies showing measurable outcomes (including a markdown campaign that increased profit by 12.5% and reduced average discounting by 4–5 percentage points), to help you frame business cases and prioritise roadmap items.
Commercial & merchandising leaders
Merchandisers, category leaders, pricing and markdown managers, inventory and planning leads, ecommerce and trading heads, and commercial finance partners who need to make faster, better pricing and markdown decisions in a volatile retail environment.
What you will take away:
- A practical view of how to make faster, better pricing decisions in a retail environment shaped by AI agents, social media, and real‑time shifts in customer behaviour.
- Concrete ideas for improving markdown outcomes without relying solely on instinct, blanket discounting, or reactive competitor matching.
- A clearer understanding of customer response through elasticity and experimentation, and what that means for everyday pricing, promotions, and markdowns.
- Guidance on how to balance margin, sell‑through, and inventory risk more effectively using data‑driven methods rather than one‑off exercises.
Turn your retail data into smarter pricing decisions
Join our online seminar to see how leading retailers are forecasting and experimentation to set smarter prices and better markdowns.
Speaker
Hear directly from the industry expert.
Marc Nientker, Operations Lead | ADC
Marc Nientker leads pricing and econometrics work for clients in retail and transportation. He specialises in building causal pricing and markdown engines from observational data, combining robust econometric modelling with scalable machine learning architectures. Marc’s projects focus on turning complex models into fully automated pricing and revenue‑optimisation tools, validated through experiments and embedded in clients’ day‑to‑day decision processes. He regularly works with data science and commercial teams to translate model outputs into actionable pricing, inventory, and promotional strategies that deliver measurable business impact.
Marc's LinkedInEvent details
- Date and time: Tuesday 14th of April | 9:00 - 10:00
- Location: Online
- Duration: 1 hour
Get in touch
Questions about the event? Contact Jacob Vestergaard at jacob.v@adc-consulting.com