DIEBOLD NIXDORF AI NAVIGATOR
VISIT PART 1 of "THE DN AI NAVIGATOR"
The Race for AI Transformation + Next Generation of Retail is underway.
What Solutions Will Lead The Way?
Who will guide massive enterprises through this new challenge and help guide them to solutions that actually solve challenges?
WELCOME TO THE DN AI NAVIGATOR
“The Global Artificial Intelligence (AI) in Retail Market was valued USD 7.3 Billion in 2023 and projected to reach USD 51.5 Billion by 2030,
growing at a CAGR of 32.2% during the forecast period of 2023-2030″
Ecosystems
A TRANSFORMATION IN MOTION
Retail is challenged by rapid and confusing commercialization of Artificial Intelligence. The entire industry reflects this massive shift. This recent piece by Salesforce lets us know 81% of respondents have committed AI budgets.
While nearly all have communicated commitment to AI, very few demonstrated that they can deliver value and can clearly understand a path forward.
Legacy businesses must demonstrate market leadership to lead and thrive in this new landscape as newcomers race forward.
The market is being defined now and adding massive value, now. It is critical that brands and businesses participate and lead.
THE CHALLENGE
DIEBOLD NIXDORF is one of the premier hardware providers in the retail space. They are acutely focused on a seamless customer journey specifically around checkouts and cash-wraps. The amount of data and insights into purchase path and transactions they have holds tremendous opportunity for the future of this great company.
As the world of retail transitions into a data lead, AI powered operating systems DIEBOLD NIXDORF is creating a whole new world of solutions that complement their current business. How they start building this brand profile and the complementary solutions is critically important.
Their Brand must lead during this critical period and help define how AI will shape applications and solutions in their market.
THE SOLUTION
An outstanding DIEBOLD NIXDORF team is already shaping the future of their retail solutions. They need a fresh innovative concept that is additive to their current brand platform and lets customers know they are a company that is leading the way to the next generation of solutions.
The Science Project worked hand in hand with the DN team to introduce a new brand platform called the DN AI Navigator. The “Navigator” is designed to be a flexible and durable tool that guides customers to a current suite of solutions DN currently has. It collects prospect data, drives demand generation and introduces a framework for DN’s future solutions.
Within 3 short months, The Science Project and the DN Team launched The DN AI Navigator at The Harvard Club event January 13th for a single night to a closed audience of executives.
The DN AI Navigator launch communicated the basic concept of the new platform with a small website, video, print piece and was a success setting up the next generation of DN’s leadership in Artificial Intelligence and Solution creation.
3 Use Cases for AI in Retail
The following answers were spell checked by AI 😉
- Real Personalization: Our attempts at true personalization in the past have suffered from constraints around data, context and privacy. AI bridges many of those gaps for us. The road ahead will be more personalized as brands and retailers create new conversations and interactions with their customer, talking with the, not at them will build relationships and data records. AI-driven recommendation engines can increase conversion rates by up to 30%, tailoring product suggestions in real-time. This creates real value.
- Inventory Management: The tangled morass of inventory must be the largest cited challenge that I run across. This is something I have always wished I could solve. AI is making demand forecasting and stock tracking more accurate. AI-driven demand forecasting can improve accuracy by up to 50%, helping retailers anticipate sales peaks and dips, even accounting for external factors like weather, holidays, and economic changes.
- Computer Vision for Enhanced Customer Service: In-store, AI-powered computer vision systems analyze customer movements, behavior, and engagement, providing data on hot zones and product interaction. For example, some stores use AI-driven cameras to identify when a customer is struggling to find a product or needs assistance, notifying staff to step in. This technology can also enhance loss prevention, monitor shelf stock in real time, and create seamless checkout experiences, like Amazon’s “Just Walk Out” stores.