More data won't make your AI smarter (here's what will)

More data won't make your AI smarter (here's what will)

Your company is collecting more customer data than ever. You know every click, session, purchase, and support call. On paper, your AI agent should know your customers better than your best rep does.

There’s a disconnect, though.

Twilio research found that 99% of companies say something is stopping them from understanding their customers. No, that’s not a hyperbolic claim either — that number is backed by our survey of 7,652 consumers and 660 business leaders across the globe. That something stopping them isn’t collection, storage, or volume. 

It was connecting data across channels (cited by 48%).

The data already exists. It just isn’t working for your business.

Data collection was never the problem

Most organizations spent the last decade building infrastructure to capture billions of data points. That project worked. Data warehouses are full.

More often than not, that’s where data stopped. 

What didn't get built was the layer that makes any of it usable in the eight seconds an AI agent has before a customer gives up. The data activation layer.

Businesses seem to know it. Connecting customer data climbed from the third-place priority last year to the number one priority this year. It's the fastest-moving item on the list.

What data-rich and context-poor looks like

From the outside, a disconnected stack often shows up like this:

• 74% of consumers repeat themselves when interacting with an AI assistant.

• 76% say the human agent has little-to-no context about their issue, so they repeat themselves again.

• 71% will abandon a conversation if an AI agent fails to recognize who they are.

Almost ¾ of your customers leave when an AI agent fails to recognize them—that makes recognition a non-negotiable part of the customer experience. 

Our report Inside the Conversational AI Revolution adds some more color: 

• 91% of brands have seen customer satisfaction drop because of an AI misstep

• 40% of consumers say AI repeats itself or gets stuck in loops.

• 39% describe AI agents as helpful.

That’s not necessarily a knock on your AI agents, but it’s validation that AI agents across the board can do better. Because we know (and you know) these tools can automate, accelerate, and personalize customer experiences at scale…when deployed with the right technology stack.

The biggest thing hurting the conversations is lost context between channels or interactions. When you read that, you might be tempted to blame the AI or the large language model (LLM), but that’s not what’s happening. 

No, the problem is your agents, humans, and channels aren’t sharing real-time data.

3 things that make your AI agent smarter

You don’t need more data to improve your customers’ experiences. You need:

1. Continuity across channels

2. Freshness

3. Retrieval at the right moment

1. Continuity across channels

Customers engage your brand across channels. They might start in a web chat, migrate to SMS, and call two days later thinking they're having one conversation. But most systems record three separate ones.

Twilio Conversations treats those touchpoints as a single lifecycle, so context follows the customer instead of resetting at every channel boundary. That's what removes the repetition, and repetition is the most cited complaint in the data.

2. Freshness

A profile assembled last night is wrong by the time a customer calls about something new that happened this morning.

Twilio Conversation Memory syncs new interaction details into existing profiles in real time, so both AI and human agents work from the current view. Stale context produces confident wrong answers. And that’s worse than a delay or admitting uncertainty.

3. Retrieval at the right moment

You have the customer history in your system, but can you surface the relevant part of it mid-conversation?

You want an AI agent that pulls the specific policy, last order, and open ticket, and does it while the customer is still typing. Twilio Conversation Intelligence surfaces approved FAQs, policies, and product docs alongside customer history, which keeps answers grounded in facts your team signed off on.

You have the data. Now connect it.

84% of brands say their AI agents already recognize returning customers and access brand history effectively, but only 40% are designing personalization around that history.

That's a 44-point gap between having the capability and using it. Most of those companies don't need another system. They need the system they have wired into every interaction with conversational AI.

The instinct when AI underperforms is to feed it more. More sources, more history, more fields. This rarely helps because the failure usually happens at a channel boundary rather than a data boundary.

Start somewhere smaller. Pick the handoff where customers most often repeat themselves and make context survive it. Then the next one. Every gap you close removes a reason for someone to abandon the conversation.

Get all the numbers you need to measure twice, build once with our Customer Insights Series report: Navigating the Data Deluge: A Compass for Customer Context. Or start building with Twilio for free.

Frequently asked questions

Why isn't my AI agent using the customer data we already have? 

Twilio research points to connection over collection. 48% of companies name connecting data across channels as their top obstacle. 84% of brands say their AI can access history but only 40% design personalization around it.

Why does my AI keep asking customers to repeat themselves? 

Twilio research found 74% of consumers repeat themselves to AI agents, usually because context doesn't survive a channel or session boundary. Twilio Conversations treats touchpoints as one lifecycle so the thread carries over.

What data does an AI agent need to be useful?

Twilio recommends three things: (1) continuity across channels, (2) profiles updated in real time, and (3) retrieval of the relevant history mid-conversation. Volume of stored data matters less than whether the right details surface at the right time.

Will a CDP fix my AI context problem? 

Not by itself. Twilio research shows 67% of businesses are investing in a CDP, but 84% already report their AI can access customer history. However, only 40% use it for personalization. The gap sits in data activation rather than data storage.

How much does poor context cost? 

Twilio research found 71% of consumers will abandon a conversation if an AI agent fails to recognize them, and 91% of brands have seen satisfaction drop from an AI misstep.