Businesses are trying to become more profitable. Rather than only going for bigger market share, they are focusing on sustainable growth and improving their bottom line.
AI is obviously the topic of our time and the key to delivering efficiency in the future. No matter what customer you engage with, expect the topic of AI to be touched on in some form.
Business Challenges in B2B and B2C
The challenges companies face today are as diverse as their industries, products and business processes. But there are some general issues faced by most players in the market.
Good Data is a Challenge
AI is the holy grail of future business success and the solution to many of the challenges companies face. However, today, we’ll address a critical reality that most have to deal with. Most data is not AI-ready, and there are key reasons for that divide between where customers are now and where they need to get.
Data Silos: Data often resides in disparate silos. This means it's scattered across various systems, departments, or platforms that don’t communicate effectively. Silos create fragmentation, making it hard to get a complete picture of end customers.
Different Data Models: Data is often stored in different formats or models. This lack of standardization complicates its integration and usability for AI solutions.
Lack of Connection to Business Processes: To drive real impact, data must be integrated into core business processes—like ERP, supply chain, or HR systems. Without this connection, even the best AI tools can’t generate actionable insights.
Data Silos - an Old Problem
The issues around data silos are not new. Many organizations have tried to integrate this data before, to integrate business processes. They mostly did this by using middleware, but this brings its own challenges.
The recent growth of the customer experience market has only aggravated the problem. More and more CX solutions have been coming onto the market to tackle specific use cases or problems.
Each one collecting more data, but mostly also coming with its own integration requirements, data model and data silo. This has made it even harder to unify data across solutions and processes, ultimately making it even more difficult to offer great customer experiences.
Summary
- Meeting the high expectations customers now have when shopping digitally is challenging and requires flexibility and innovation. This, in turn, drives up operating costs, putting pressure on companies' profit margins.
- AI promises significant business success in tackling the challenge of improving top-line growth and significantly reducing the cost of doing business. However, most organizations struggle with data readiness.
- To dazzle your customers and effectively use AI, it’s essential to break down silos, unify data across all platforms, and tie it to business processes.