The 3 Key Elements of a Successful Omnichannel Strategy 

Regardless of where people shop or how they buy, they want a seamless customer experience, start to finish. They want to feel that their customer journey, from advertisements and shopping to purchase and delivery, is being delivered by a single entity, no matter how many systems are involved behind the scenes.

What they want is an omnichannel experience, even if they don’t know what the term means.

Retailers can deliver that seamless experience, but to do so effectively they need to understand and prioritize the key elements of an omnichannel strategy, recognizing how integration, automation and artificial intelligence work together.  

Omnichannel Outperforms Multichannel

Omnichannel represents the next step in connecting with customers, evolving past the multichannel approach still used by many retailers.

Multichannel, as the name suggests, combines multiple channels, such as TV, social media and email, to reach customers, but not necessarily in a unified way. For example, the message in one format may be different from the message in another. Multichannel also tends to be product centric and may emphasize specific channels, resulting in an inconsistent experience for the customer.

Omnichannel takes a unified, customer-centric approach that integrates the customer experience across all channels, regardless of whether those channels are online or offline. It delivers a consistent message across social media, email, pop-ups and other channels. It allows sellers to follow up with customers about their choices while shopping online, or text a customer about promotions while the customer is in-store.

The Keys to Creating an Omnichannel Experience

Pursuing an omnichannel strategy starts with the integration of data, builds on that foundation to automate the business, and flourishes by knowing how — and how not — to use AI.

Automation is the overarching capability, with integration as one of its foundational components. Together, they can deliver higher data quality, which spurs organizations to be more diligent about business processes and change management. Then, transformative AI as another tool of automation can be added on top of that foundation. Too many organizations don’t get this right, looking to AI as the answer without first putting the foundational pieces in place.

To create a fully omnichannel experience that leverages AI effectively, you need to integrate systems to generate usable data. AI requires clean, quality data because imperfect data creates unreliable AI. One of the biggest barriers to achieving this clean, quality data is a lack of fully integrated systems, leaving data in silos throughout an organization.

A lack of integration can be at the root of why some retailers haven’t been able to move toward an omnichannel strategy. Midmarket organizations, for example, have shown a strong interest in AI, yet it hasn’t made much of an impact to their businesses beyond surface-level adoption of large language models (LLMs). They need better data quality and automation to make it work.

Setting the foundation for AI is just the first step. Even when organizations are using AI effectively, they also need to ensure they're using it in a way that enhances the customer experience without hindering it.

AI as an Accelerator Rather Than a Replacement

There's a big difference between using AI to replace people and using AI as an accelerator. Companies need to understand the right scenarios for each approach.

AI excels at certain tasks, but it's not perfect. It can still make mistakes, providing inaccurate or incomplete answers. ChatGPT-4, the latest iteration of OpenAI’s widely used model, takes a significant step forward in understanding context and tone, but it’s still not a person. It lacks cognitive human ability to understand the subtleties and nuances of interactions with people, which can make all the difference in delivering a truly satisfying customer experience.

Retailers need to take a critical look at how they use AI. Making recommendations on an e-commerce site based on prior purchasing patterns is a highly effective use of AI. You don’t need a person curating that, and the AI will make very insightful decisions.

But in a high-touch sales scenario, turning the job over to AI could be a costly mistake because AI could fail to pick up on the nuances involved in true human interactions. That’s a clear case in which AI works better as an accelerator. AI’s ability to analyze data across multiple sources while recognizing hidden patterns can save a human representative a lot of time on research, but the interaction with the customer would still need to leverage the cognitive power of the person.

For example, at Celigo, one of the AI solutions that we've built helps accelerate technical product research across multiple sources for customer-facing team members. The AI can rapidly search across collaboration channel transcripts, knowledge base articles, product documentation, and customer support tickets to find the best answer. The AI does that job well but the solution is best used when a human can review the answer, provide critical thinking whether it's appropriate, and then deliver that answer to the customer with guidance on how to apply it. In that case, combining AI’s ability to handle the time-consuming grunt work with human insights increases efficiency and the customer experience at the same time.

Using AI to complement, rather than replace, people also works well with creating unique product descriptions, which is something companies often fail to invest enough effort into. AI doesn't create original content; it can only regurgitate what you already have. And unimaginative descriptions don’t stand out, leading to poor search engine rankings. But the AI can gather data and speed up the writing process being done by real people, ultimately accelerating the creative process.

Conclusion

A customer should never be conscious of your systems. All of that should be invisible to them. A properly implemented omnichannel strategy should give the customer the sense of dealing with a single entity that provides consistent service across all channels, via smooth interactions that not only deliver what the customer wants but also anticipates what they may need and reaches out when something is delayed. When done well, you can anticipate problems before they occur and provide solutions before they become problems.

The key to success starts with understanding the hierarchy of automation, integration and AI, and how they best work together.

Mark Simon is the vice president of strategy at Celigo, an integration-platform-as-a-service (iPaaS).