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Software strategies for seamless omnichannel retail experiences

You can't personalize experiences when customer data resides in six different systems that don't communicate with each other.

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Most retail companies spend a fortune duct-taping their customer support systems together. You have one vendor for web chat, another for voice, a third for SMS, and somehow you’re supposed to make all of that talk to each other. The cost of integration gets so heavy that companies end up spending more time managing their tech stack than serving customers.

Meanwhile, 76% of consumers expect consistent experiences across every channel they use. Another 81% now view AI as necessary for modern customer service. Customers don’t care about the number of tools or integrations behind the scenes, except when the experience breaks. They want the same quality of service whether they’re texting, calling, or chatting on your website.

The problem isn’t that developers are building bad tools. It’s that we’re still building point solutions when what retail needs is a unified architecture.

The fragmentation problem

Here’s what fragmentation looks like in practice. A retailer uses one company for their website chatbot, a different vendor for phone support, another for SMS, and yet another for email ticketing. When a customer reaches out through multiple channels about the same order, each system treats it as a separate issue.

For developers, this means maintaining separate APIs for each vendor. Data lives in different formats across different databases. When you need to update customer information, you’re writing to five different systems and hoping they sync correctly.

The impact shows up fast. Customers wait longer because agents hunt across systems for context. Support teams get burned out toggling between platforms and manually copying information.

I’ve seen companies running seven or eight different AI vendors just for their contact center. Seven separate training processes. Seven sets of API documentation. The team bandwidth required to keep those systems running ate into time they could have spent improving customer service.

What unified architecture looks like

Let’s look at PacSun as an example. The clothing retailer was dealing with call center overload from basic product questions and post-purchase support. They integrated web chat and SMS into a single system. Now 85% of customer inquiries get handled without agent intervention.

The technical requirements for this work are straightforward. You need a single customer view across all channels. No more separate databases. When a customer moves from chat to SMS to voice, the context travels with them. Your escalation path is just as important as your AI quality. When automation can’t handle something, the handoff to a live agent needs to be smooth and include full context.

Analytics feedback into every touchpoint in real-time. If customers keep asking about a specific product issue on chat, that insight should inform your voice responses and email automation immediately.

For PacSun, this approach drove 33% of shoppers to opt into SMS notifications. Personalized product recommendations converted at 19%. And the system runs 24/7, which matters because over half their chat interactions happen outside business hours.

Building vs. integrating

For ISVs, or Independent Software Vendors, the decision comes down to whether you’re building another point solution that adds to the integration problem or thinking in platforms.

If you’re unsure, these questions should help guide you to your answer:

  • Can your AI agent hand off to a human agent without dropping context?
  • Does customer data actually travel between channels, or does each touchpoint start from scratch?
  • When a customer calls after chatting on a retailer’s website, does the phone system know what already happened?

Eighty-eight percent of CX leaders now say personalization is a priority. You can’t personalize experiences when customer data resides in six different systems that don’t communicate with each other. It requires a unified data layer.

Retail’s omnichannel problem is a developer problem. And they can fix it by building systems where integration and consistency aren’t afterthoughts. Customer expectations aren’t going backwards. The platforms that treat every channel as part of one experience will win. Everything else is just more duct tape.


David Karandish

David Karandish is Founder & CEO of Capacity – an enterprise SaaS company headquartered in St. Louis, MO. Capacity is a support automation platform that uses AI to deflect emails, calls, and tickets so internal and external support teams can spend more time doing their best work.

Prior to starting Capacity, David was the CEO of Answers Corp. He and his business partner Chris Sims started the parent company of Answers in 2006 and sold it to a private equity firm in 2014 for $960m.

David sits on the boards of Create a Loop (a computer science education non-profit tackling the digital divide by teaching kids to code). David was also an early investor and board member at Nerdy (NYSE: NRDY), an on-demand, real-time learning platform in the ed tech space.

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