Ask a typical enterprise marketer to draw their martech stack on a whiteboard, and you'll usually see a customer data platform (CDP), various marketing automation platforms, and an analytics and attribution layer.
According to Klaviyo’s 2025 State of B2C Marketing Report, the average B2C brand’s tech stack is made up of 6–15 tools. But more tools doesn't necessarily mean more value. Each one adds cost, complexity, and another integration to maintain.
Consolidation, on the other hand, can pay off with personalisation: when your entire martech stack is pulling from the same customer data, every brand interaction is based on a real-time single source of truth about the customer.
Personalisation leaders achieve compound annual growth rates that are 10% higher than those who are behind, according to the BCG Personalization Index.
Keep reading to find out how to unify your customer data, AI, and marketing automation channels so they’re working as one.
What is enterprise marketing automation?
Enterprise marketing automation is an all-in-one platform that unifies customer data, AI, and every marketing channel, so large B2C teams can plan, run, and measure personalised campaigns at scale.
When all your marketing channels and AI agents are working from the same customer profile, enterprise teams can scale customer experiences in ways that remain relevant and personalised to the customer.
Say a customer bought an espresso machine from you last month, then they return to your website to browse grinders. They open a web chat to ask, “Which grinder should I get for my machine?”
An AI agent that can read one customer profile with browsing and purchase information can answer, “The burr grinder you were looking at pairs well with the machine you bought in June. Want me to add it to your cart?”
How enterprise automation differs from SMB automation
Small- and mid-size business (SMB) marketing automation works within a smaller scope than enterprise automation.
An SMB scales channels and personalisation across a smaller number of product lines, usually for a single brand. There are fewer regional differences to account for and no need to coordinate automations across a portfolio.
Enterprise automation often requires data orchestration across multiple brands or regions at much higher volume. Enterprise teams are also routing campaigns through more stakeholders, IT and data teams, and compliance and legal review. Each handoff has the potential to delay campaigns and automation set-up or revision.
Those conditions translate into requirements an SMB rarely has to think about. Enterprise teams need a data layer that keeps all brands and regions working from the same real-time customer profiles, and sending infrastructure that holds up at peak volume.
How a consolidated stack differs from a fragmented one
A fragmented stack grows tool by tool: a CDP here, a channel tool there, each with its own customer database requiring syncs with the rest.
A consolidated stack, such as a B2C CRM, starts from one shared customer profile housed in a CDP, with marketing automation and AI agents embedded within the platform.
You'll feel the differences in 5 places:
Area | Fragmented | Consolidated |
|---|---|---|
Data architecture | Synced databases | One customer data platform |
Customer profiles | Batch or nightly syncs | Real-time updates as customers take actions |
AI agents | Static rules per channel | Dynamic based on customer data and documentation |
Channel coordination | Sequenced tool by tool | One profile drives every channel |
Team dependency | IT and vendor tickets | Marketer-owned |
How unified data streamlines AI and channel functionality
When your data, AI agents, and marketing automation run on one platform, each piece informs the other.
Customer profiles update in real time, AI can serve customers based on their actions and preferences, and marketers can launch on new channels themselves.
Real-time customer profiles
A real-time customer profile is one dynamic record of each customer: their purchases, browsing behaviour, email and text engagement, support conversations, etc. When customers take actions or state preferences, their customer profile is refreshed the moment something changes.
That shared profile is what scales personalisation among enterprise brands, whether they’re targeting 1,000 customers or 100,000. When your segments, automations, and campaigns are all referencing the same record, you can make more relevant product suggestions at optimal times on each customer’s preferred channel.
For example, let’s say a customer browses a trail shoe and leaves without buying. The browse event is recorded on their profile, added to last season's orders and their text message engagement.
That event triggers a browse abandonment text message flow featuring the exact shoe they browsed. If the customer ends up buying the shoe in-store that afternoon, the purchase is recorded before a redundant discount follow-up goes out.
When all your brands and regions run on the same profile architecture, each team's automations respond to local behaviour using the right languages, currencies, and consent rules, while performance rolls up to one view of the portfolio.
Data warehouse and platform integration
Consolidating your marketing stack doesn't mean starting from scratch with your data warehouse. It just means you’ll be able to better enhance your marketing automation efforts with more insights from your data warehouse, with less dependence on your data science and IT teams.
Some teams maintain their marketing platforms as their primary data store, with a built-in CDP handling identity resolution and segmentation in one place. Others keep platforms such as Snowflake or BigQuery as their system of record, and use an advanced CDP as their data activation layer, syncing warehouse tables directly into live customer profiles.
For your team and your customers, that translates to:
- Faster action on insights: Marketers can manipulate and activate warehouse data themselves, so an insight can become a live segment the same day.
- More accurate attribution: Warehouse models and marketing engagement read from the same records, so you can see which messages and channels drive revenue and allocate spend with more confidence.
- More nimble personalisation: Enriched attributes, like propensity scores from your data science team, land on live profiles where marketers can use them immediately for flows and campaigns, which can mean more revenue from more relevant sends.
AI agents trained on customer data
Effective AI marketing is trained on live customer data and brand documentation. That training shows up in 3 ways:
- Predictive analytics: Predictive analytics include predicted lifetime value (LTV), churn risk, and expected date of next order. Every Man Jack, for example, set their reorder flow send on—or slightly before, or after—each customer’s unique predicted next order date. Within 90 days, predictive analytics segments drove 12.4% of their Klaviyo revenue (EN).
- AI marketing agents: When an AI marketing agent is informed by your customer data, campaign history, and performance signals, it can spot revenue opportunities a human marketer scanning dashboards may not see. Marketers can use AI agents to draft launch-ready campaigns based on those suggested opportunities in minutes, and teams save time because all they need to do is approve what goes out.
- AI customer agents: An AI customer agent learns more about each customer each time they engage, and all of that data gets stored in their profile. This is how AI agents are able to answer questions and make product suggestions that customers actually find useful.
Marketing deployment without support tickets
Omnichannel marketing at enterprise scale means email, SMS, RCS, mobile push, WhatsApp, and on-site experiences across brands and regions all run from one customer profile.
But for many enterprise teams, channel expansion means engineering time. When basic automations and cross-channel campaigns require custom scripting, marketers can stop asking for the small changes that can make big revenue differences.
When marketing regains that autonomy, the small changes your team stopped asking for start happening again. You notice an abandoned cart flow underperforming on Tuesday, adjust the trigger, the delay, or the offer that afternoon, and watch next week's numbers move.
A test that used to feel too small to bother engineering with, like a new subject line on a win-back flow or a text message added to a launch sequence, becomes a short task, so more of those tests actually run.
For example, Helen of Troy, the consumer products brand behind OXO, Osprey, and Hydro Flask, had email and SMS in one platform, but using the two channels together—say, to create a multi-channel flow—required a prohibitive amount of developer support.
Now, Helen of Troy’s home and outdoor division uses Klaviyo to store first-party data and share it between marketing channels. For example, they use Klaviyo integrations with Facebook, Google, and TikTok to build lookalike audiences and exclude current email and SMS subscribers from paid acquisition campaigns.
The consolidation saves the team hundreds of IT tickets per year and has reduced total cost of ownership (TCO) by more than 40%.
How to evaluate enterprise marketing automation platforms
Evaluating an enterprise marketing automation platform comes down to whether you can deploy marketing messages based on one shared customer profile.
In practice, that means centralized customer data with embedded marketing automation, AI agents, and analytics and attribution models.
Unified data
- One shared profile per customer: Orders, browsing behaviour, marketing engagement, service conversations, preferences, loyalty status, etc. are housed in a single record.
- Real-time updates: Profiles and segments change as customers act.
- Direct warehouse sync: Data moves between your CDP and other platforms such as Snowflake, BigQuery, or Databricks without an engineering ticket.
- Custom properties: The customer profile extends to whatever your business prioritises, like subscriptions, reservations, or households.
AI marketing agents
- Custom training: Your AI agent should be trained on your own business intelligence such as your customer data, product data, campaigns, and performance history.
- Plain-language performance queries: You can ask how a campaign or flow is performing and get a direct answer without pulling reports.
- Opportunity detection: The AI surfaces what's working, what isn't, and what to launch next based on your own data, including flows, segments, and channels.
- Guardrails and audit trails: Humans set the boundaries and sign-off points, and there's an audit trail to review.
Omnichannel consolidation
- One campaign builder across channels: Email, SMS, push, and WhatsApp are built and scheduled from a single interface.
- Channel affinity: Your messages are automatically routed to the channel each customer engages with the most.
- Mobile marketing: You’re able to easily grow on WhatsApp, push notifications, and RCS under one roof.
- Marketer-owned launches: Your team can add a channel or launch a campaign without engineering support.
Marketing analytics
- RFM analysis: Segment customers by recency, frequency, and monetary value, and automate outreach based on loyalty and churn risk.
- Funnel analysis: Visualise the journey by segment, channel, and timeframe to find the biggest conversion drop-offs.
- Multi-touch attribution: Revenue reporting lives in one dashboard and credits how channels, campaigns, and flows work together, with attribution windows you control.
Enterprise marketing automation in action
Dollar Shave Club cuts campaign set-up time by 60%
When Dollar Shave Club decided to consolidate their CRM stack, parts of their marketing calendar ran at the speed of their engineering queue: hand-coded HTML for every email, weeks of lead time for data for segmentation, and personalisation that meant manual work across systems that didn't talk to each other.
The team replaced multiple tools with Klaviyo email marketing automation, Klaviyo Data Platform, and Klaviyo forms. Campaign set-up time dropped more than 60% (EN), and the brand has sent 237 million email and SMS messages in the last 12 months.
The consolidation also opened up personalisation the old stack couldn't support: subscription up-sells and targeted SMS acquisition.
Marc Fisher Footwear grows SMS revenue 46% and migrates 6 brands
Marc Fisher Footwear managed several brands on another platform, where SMS segments couldn't be saved and had to be rebuilt from scratch every time.
Worse, the brand needed to elevate their premium portfolio toward a full-price, personalised experience, but their email and SMS strategy could really only accommodate promotional offers and discounting. This is because, with no built-in customer data platform, segmenting and automation demanded a lot of time-sucking manual work.
As a result, Marc Fisher decided to consolidate email, SMS, and push notifications for 6 brands to Klaviyo. RFM-based segmentation now allows the brand to take a more full-price, brand-first position with loyal customers while reserving discounts for customers at risk of churn. Channel affinity logic also routes each message to the channel where each subscriber is most likely to engage. In the second half of 2025, SMS revenue across the portfolio grew 46% YoY (EN).
Scale personalisation with Klaviyo enterprise marketing automation
Klaviyo is the autonomous CRM built for B2C, bringing real-time customer data, analytics, and AI agents together on one platform.
- Unified customer data for every channel: Advanced Klaviyo Data Platform keeps every channel working from the same real-time customer data, unifying, cleaning, transforming, and enriching it however you need. Define custom properties and manipulate customer data to create truly personalised experiences that drive more revenue.
- AI campaigns built by Composer: Composer is built inside Klaviyo and powered by your customer data, campaign history, and performance signals. Describe the outcome you want in plain language, and Composer builds a launch-ready campaign. Nothing goes live without your sign-off.
- Omnichannel marketing: Email, SMS, RCS, mobile push, WhatsApp, and on-site experiences all deploy from the same customer profile. Your marketers build the campaigns and flows in a visual, no-code builder, so even complex, multi-step logic doesn't require a developer.
- Analytics and attribution: Klaviyo Marketing Analytics show the full customer journey and credits revenue across channels with multi-touch, omnichannel attribution. When you spot an opportunity, you can act on it quickly.
- Scale and compliance that hold up under review: On an average day, Klaviyo processes 2.5 billion events, sends 1.1 billion emails, and handles 1.6 billion API calls all on a single streaming architecture with 99.9% uptime. There are no data caps and no ceiling on send volume, even on Black Friday. Brands and regional teams can be managed from one place, with shared assets, cloned campaigns, and rolled-up analytics. Klaviyo is ISO 27001 and SOC 2 Type II certified, with RBAC, SSO, and GDPR/CCPA compliance built in.
See how Klaviyo can speed up marketing campaigns and automation set-up. Get a demo