ChatGPT answers, unedited

Yes. If the main problem is “I need to express complicated inclusion/exclusion logic over purchase history + email behavior without writing SQL,” there are several good options.

Best fits

• Hightouch — probably the strongest fit if you have your customer/order/email data in a warehouse. Its Audience Builder supports nested AND/OR logic, exclusions, relationships, events, reusable traits, and audience membership. For example: “bought product A in the last 12 months AND clicked an email in 30 days, BUT has not bought product B.” Hightouch

hightouch.com

• Klaviyo — excellent if your data primarily lives in an ecommerce/email stack. Its segment builder supports inclusion/exclusion based on events, event properties, profile properties, and time windows, with up to 100 conditions per segment. It also has purchase-derived metrics such as historical CLV, predicted CLV, number of orders, and average time between purchases. Klaviyo Help Center Klaviyo Help Center

The limitation is that some deeply nested event data can't be used directly in segmentation. Klaviyo Help Center
klaviyo.com

• Bloomreach — particularly interesting for ecommerce. It supports behavioral/event-based segmentation, custom metrics, purchase history, CLTV, real-time segment changes, and activation into email/SMS/ads/etc. Bloomreach Documentation Bloomreach

bloomreach.com

• Mailchimp — has an advanced segment builder with nested AND/OR logic and unlimited conditions, including purchase and email engagement data. I'd consider it more of an email-marketing solution than a sophisticated customer-data layer, though. Mailchimp Mailchimp

mailchimp.com

The distinction I'd make

If your desired UI is something like:

Include:
Customers who purchased X ≥ 2 times
AND purchased within the last 180 days
AND clicked an email in the last 60 days

BUT exclude:
Anyone who purchased Y in the last 30 days
OR anyone who received campaign Z more than 3 times without clicking

AND additionally:
Customer lifetime spend > $500

then Hightouch is the one I'd investigate first if you have a warehouse/data platform. Its relational filtering is particularly relevant because you can say things like “has Purchase where amount > $100” rather than flattening everything into customer properties. Hightouch

If you don't have a warehouse and want marketers to build these audiences directly from Shopify + email behavior, I'd look at Klaviyo or Bloomreach first.

If you tell me where your purchase data and email history currently live (e.g. Shopify + Klaviyo, Salesforce + Marketo, Snowflake, Postgres, etc.), I can narrow this down to the 2–3 platforms that fit best and show you how each would represent a really nasty inclusion/exclusion rule.

Yes. If by “complex purchase and email history” you mean rules like:

Include customers who bought Product A 2+ times in the last 180 days AND opened an email in the last 30 days, BUT exclude anyone who bought Product B in the last 14 days OR unsubscribed.

There are a few good options, but Hightouch Customer Studio is probably the closest match if the logic is genuinely complex.

1. Hightouch Customer Studio — best for complex logic

Hightouch Customer Studio

Hightouch lets marketers visually construct audiences on top of warehouse/customer data. Its builder supports AND/OR/nested Boolean logic, event conditions, related purchase records, existing audiences, and reusable traits. hightouch.com

Importantly, it supports nested purchase logic, e.g.:

• Customer has ≥2 purchases in 90 days
• where the purchase contains Product X
• AND customer opened an email in 30 days
• AND customer is not in a churned audience
• EXCLUDE customers with a purchase of Product Y in the last 7 days

It can also turn natural-language instructions into the audience definition, so you can essentially describe the segment and then inspect the generated logic. hightouch.com

I'd pick this if your data already lives in Snowflake/BigQuery/Databricks/etc.

2. Klaviyo — best if email is the center of the workflow

Klaviyo

Klaviyo has a very good native segment builder. You can combine purchase events, email opens/clicks, profile properties, subscription status, and negative conditions with AND/OR logic. help.klaviyo.comhelp.klaviyo.com

For example:

Include

• Placed Order ≥ 2 times
• in last 180 days
• AND opened email ≥ 1 time in last 30 days

Exclude

• Placed Order for Category X in last 14 days
• OR is suppressed/unsubscribed

It supports up to 100 conditions per segment, and segments dynamically update as people meet or stop meeting the criteria. help.klaviyo.comhelp.klaviyo.com

The limitation is that once your segmentation starts involving complicated relationships between arbitrary purchase records, multiple data sources, or reusable business logic, a warehouse-centric tool like Hightouch becomes more attractive.

3. If you're building this as a product

If you're asking because you want to build a platform that makes this easier, I think there's an interesting product opportunity here.

The UX I'd aim for is something like:

INCLUDE
  └─ Customers
      ├─ who purchased
      │    ├─ Product = "A"
      │    ├─ at least 2 times
      │    └─ within last 180 days
      │
      └─ AND
           └─ engaged with email
                ├─ opened ≥ 1
                └─ within last 30 days

EXCLUDE
  └─ Customers
      ├─ who purchased Product B
      │    └─ within last 14 days
      │
      └─ OR
           └─ unsubscribed

The key UX distinction I'd make is separating “Include” and “Exclude” groups rather than making users mentally construct complicated combinations of negative conditions. Klaviyo itself warns that negative conditions combined with OR can produce unintuitive results. help.klaviyo.com

If you tell me what your underlying data looks like (e.g. Shopify + Klaviyo, Salesforce + Braze, warehouse tables, etc.), I can point you to the best existing platform—or map out what the ideal rule builder would look like.

Yes. If by “complex purchase and email history” you mean rules like:

Include customers who bought Product A in the last 180 days AND have opened an email in the last 30 days, BUT exclude anyone who bought Product B in the last 14 days OR received Campaign X more than 3 times without clicking.

There are a few platforms worth looking at:

1. Hightouch Customer Studio — probably the best fit for complex logic

Hightouch Customer Studio is particularly interesting if your customer/purchase/email data lives in a warehouse such as Snowflake, BigQuery, or Postgres.

It has a visual audience builder supporting:

• Nested AND / OR groups
• Inclusion and exclusion rules
• Purchase/order relationships
• Event history and time windows
• Multiple levels of related data, e.g. Customer → Orders → Items
• Reusable traits
• Audience-to-audience inclusion/exclusion
• Previewing who qualifies
• Natural-language audience construction with AI

For example, Hightouch explicitly supports nested filtering such as finding users who have a purchase in the last 30 days containing a particular type of item. hightouch.com

The big advantage is that you aren't forced to flatten all your purchase history into a bunch of awkward customer properties.

2. Klaviyo — best if email/SMS is the center of the workflow

Klaviyo has a very capable segment builder. You can combine profile properties with behavioral events such as purchases and email engagement, and use AND/OR logic and event-level filters. help.klaviyo.comhelp.klaviyo.com

It's a particularly good choice if your data is already in Klaviyo.

The limitation is that its segmentation model is more constrained than a warehouse-native audience builder. For example, Klaviyo notes that segment filters only expose top-level event properties rather than arbitrary nested data. help.klaviyo.comhelp.klaviyo.com

3. A warehouse + Hightouch — best if you want a “customer rules engine”

If you have a substantial data warehouse, I'd seriously consider:

Shopify/CRM/email platform → warehouse → Hightouch Customer Studio → Klaviyo/Meta/etc.

That gives you a single place to define audiences rather than recreating increasingly complicated logic independently in each marketing platform. Hightouch specifically positions Customer Studio around defining audiences once from warehouse data and syncing them to multiple destinations. hightouch.com

The distinction I'd make

If you tell me what your underlying data looks like (e.g. Shopify + Klaviyo, Salesforce + Braze, Snowflake + various sources), I can recommend 3–5 platforms specifically for your use case and compare how they'd handle something like “purchased X but not Y, engaged with emails A/B, and haven't purchased in N days.”

Yes. If your goal is “build very specific audiences using purchase history + email behavior + exclusions, without having to write SQL,” there are several good options.

My shortlist

Klaviyo is probably the easiest starting point. Its segment builder lets you combine conditions with AND/OR, explicitly include or exclude people based on actions, filter individual events, and use purchase history and email engagement. help.klaviyo.comdocs.simondata.com

For example, you could express something like:

Include:
Purchased Product A at least twice
AND purchased any product in the last 180 days
AND clicked an email in the last 60 days

EXCLUDE:
Purchased Product B in the last 30 days
OR received more than 5 emails without clicking
OR is unsubscribed

Klaviyo also now supports event funnels, which lets you segment based on the sequence of events rather than simply whether events happened. That's useful for rules such as “purchased A, then received an email, but didn't purchase B afterward.” help.klaviyo.com

Where Braze gets interesting

If the segmentation you're describing is more like:

(Purchased A AND (Opened X OR Clicked Y)) AND NOT (Purchased B OR Churn Risk > threshold)

…and you have lots of behavioral data across channels, Braze is worth looking at. It has 100+ built-in segmentation filters and a SQL composer for cases where the visual builder isn't enough. www.braze.com

Simon Data is particularly interesting for really complex rules

Simon Data's Segment Builder is designed around customer/event data and supports AND/OR logic, dates, numeric conditions, strings, sets, and booleans. Its event-based segmentation can drill into individual events such as orders, including their products and values. docs.simondata.com

So if you're thinking about a visual “rules engine for audiences” rather than merely an email marketing segmentation feature, I'd put Simon Data and Braze ahead of Klaviyo.

If you tell me what your data looks like (e.g. Shopify + Klaviyo, Salesforce + HubSpot, Snowflake + email platform) and give me 2–3 examples of the complicated segments you want to build, I can tell you which platform fits best and how each would express those rules.

Yes. If your main requirement is “let a marketer build complicated include/exclude logic across purchase history + email behavior without writing SQL,” there are several good options.

My shortlist

Klaviyo is probably the first one I'd look at if this is primarily ecommerce/customer marketing. Its segment builder lets you combine things someone has or hasn't done, profile properties, and other conditions, with AND/OR logic and event filters. It can handle examples such as purchase frequency/value, specific products purchased, and email opens/clicks. help.klaviyo.comdocs.customer.io

It has also added event funnels, which allow segmentation based on the sequence of events rather than merely whether events happened. That's particularly useful for more sophisticated behavioral rules. help.klaviyo.com

For example, you could express something like:

Include: bought Product A ≥2 times in the last 180 days
AND: opened an email in the last 60 days
AND: has spent >$500 lifetime
BUT exclude: bought Product B in the last 30 days
AND exclude: anyone currently in the VIP campaign

That's pretty much the sweet spot for Klaviyo.

Where I'd look at Customer.io instead

Customer.io becomes especially interesting if your rules are more event-centric than ecommerce-centric. Its people/segment filtering can combine customer attributes, events, newsletter/message history, delivery/open behavior, and segment membership. docs.customer.io

It also introduced an AI segment builder in 2026: you can describe the audience you want and have it suggest the segment conditions based on the attributes/events in your workspace. docs.customer.io

So if your dream interface is something closer to:

“People who purchased from category X twice in the last year, haven't purchased category Y, received at least three emails but clicked none of them, unless they're a VIP”

…and you want the system to help translate that into rules, Customer.io is worth a serious look.

One important distinction

If you're asking because you're thinking about building a product/platform specifically for this, there is actually a pretty interesting gap here.

Most existing tools have a visual rule builder, but complex segmentation can quickly become a mess of nested:

AND → OR → NOT → event → timeframe → event-property filter

The interesting product could be a visual audience/rules engine where users can construct things like:

INCLUDE
  (Purchased A ≥ 2 times)
  AND (Purchased within last 180 days)
  AND
    (
      Opened email within 30 days
      OR Clicked email within 60 days
    )

EXCLUDE
  (Purchased B within 14 days)
  OR (In VIP segment)

…and then show the estimated audience count, explain why someone qualifies/doesn't qualify, and let the user inspect individual profiles.

That's substantially more compelling than just another “segment builder.”

If you tell me whether you're looking to buy something for your team or thinking about building this as a product, I can narrow this down considerably.

Yes. If by “complex purchase and email history” you mean rules like:

Include customers who bought Product A 2+ times in the last 12 months OR spent $500+, AND opened/clicked an email recently, BUT exclude anyone who bought Product B in the last 30 days or is currently in a certain campaign.

There are several platforms that do this well.

My shortlist

1. Klaviyo — probably the easiest starting point

Klaviyo's segment builder is particularly good for this use case. It supports AND/OR logic, negative conditions (“has not done”), event filters, purchase history, email engagement, custom properties, and date-based conditions. A segment can have up to 100 conditions. help.klaviyo.comhelp.klaviyo.comwww.klaviyo.com

It also recently added event funnels, which let you express sequences such as:

Purchased X → then opened email → then did NOT purchase Y

rather than merely asking whether each event happened at some point. help.klaviyo.com

And its current Segments AI can turn natural-language descriptions into segment definitions. www.klaviyo.com

2. Iterable — better if you're building very sophisticated lifecycle logic

Iterable has a query-builder approach that can combine user attributes and behavioral events, with All / Any / None logic and different comparators. Its event data explicitly includes things like purchase history and engagement with messages. support.iterable.com

It's a stronger candidate if segmentation is becoming part of a larger lifecycle/CRM orchestration system rather than primarily an ecommerce email tool.

The important distinction

If you're asking because you're evaluating a product opportunity, I'd separate these into two categories:

Klaviyo is probably the closest to “give a marketer a powerful rule builder without making them feel like they're writing SQL.” Its current segment functionality is explicitly designed around inclusion/exclusion and combining behavioral conditions. help.klaviyo.com

If you tell me what kind of rules you're trying to build (even 3–5 examples), I can also tell you which existing platform handles them cleanly vs. where you'd run into limitations.

Yes. What you’re describing is usually handled by a Customer Data Platform (CDP), marketing automation platform, or an advanced customer engagement platform with a visual audience builder. The key capability to look for is nested include/exclude logic across behavioral events (purchases, email opens/clicks, lifecycle stages, product history, etc.). help.sap.com

Some platforms that are particularly good at this:

For a typical ecommerce/email use case, you might want to build rules like:

VIP winback

INCLUDE:
- Lifetime spend > $500
- Purchased at least 3 times
- Email subscriber = true

EXCLUDE:
- Purchased in last 30 days
- Unsubscribed
- Currently in active loyalty campaign

Product launch audience

INCLUDE:
- Purchased category = "Running Shoes"
OR
- Viewed running shoes 3+ times

EXCLUDE:
- Already purchased new model
- Received launch email in last 14 days

Platforms vary a lot in how easy this is. The features I’d prioritize:

1. Visual rule builder (drag/drop AND/OR groups)
2. Segment nesting (build "VIPs", "recent buyers", etc. once and reuse them)
3. Time-window conditions ("purchased in last 90 days")
4. Event-level rules ("clicked email X but did not purchase")
5. Real-time refresh (customers automatically enter/leave segments)
6. Preview counts before activation

If you’re specifically coming from email marketing (e.g., Klaviyo, HubSpot, Salesforce Marketing Cloud) versus warehouse/data-driven segmentation (Snowflake + reverse ETL + CDP), the best answer changes. What’s your stack today (Shopify, Salesforce, HubSpot, Klaviyo, etc.) and roughly how complex are the rules?

Yes. If you mean something like:

Include customers who bought Product A 2+ times in the last 12 months OR bought from Category B, AND opened an email in the last 30 days; exclude anyone who bought Product C in the last 14 days OR received Campaign X.

There are several platforms that make this much easier than building SQL.

Best fits

Customer.io is probably the first one I'd investigate if the logic builder itself is the priority. Its current data-driven segments let you combine profile attributes, events, relationships, page events, and messaging data—including email behavior—and people automatically enter/leave segments as they satisfy or stop satisfying the conditions. It also now has an AI-assisted segment builder. docs.customer.io

Omnisend is particularly compelling for ecommerce. Its segment builder supports filter groups, nested subfilters, AND/OR logic, purchase behavior, and campaign activity; segments update automatically. docs.customer.iosupport.omnisend.comhelp.sap.com

If you're talking about really gnarly audience logic, I'd also look at Lexer. It is explicitly positioned around combining transactional, behavioral, engagement, and predictive data, with dynamic segments and conditions such as purchase recency, LTV, product affinity, and engagement. www.lexer.io

At the enterprise end, SAP's CDP has a particularly explicit include/exclude + AND/OR rule-set model, while Salesforce Data 360 has dedicated Include and Exclude segment interfaces. help.sap.com

One important distinction

If you're trying to solve "marketing segmentation", Customer.io/Omnisend are great.

If you're trying to solve "give marketers a visual interface for writing arbitrarily complex audience queries across our warehouse/CRM/order/email data", I'd look more closely at CDPs / composable audience platforms. The underlying data model matters enormously—especially whether you can express things like:

• purchased X but never Y
• purchased X 3+ times
• purchased X between 30–90 days ago
• bought from category X after clicking campaign Y
• received email X but did not open it
• opened ≥3 emails in 60 days and spent $500+
• exclude anyone who purchased the promoted SKU in the last 14 days
• (A OR B) AND (C OR D) AND NOT (E OR F)

If you tell me where your purchase data and email data currently live (e.g. Shopify + Klaviyo, Salesforce + warehouse, BigQuery + Braze, etc.), I can narrow this down to the 2–3 platforms that would actually fit your stack, rather than giving you a generic CDP list.

Yes. If by “complex” you mean things like:

Include: customers who bought Product A 2+ times in the last 12 months OR spent $500+
AND: opened/clicked an email in the last 90 days
EXCLUDE: anyone who bought Product B in the last 30 days OR is in a VIP/suppression segment

then there are several platforms that make this substantially easier than building SQL yourself.

My shortlist

Customer.io is probably the one I'd investigate first for your particular description. Its data-driven segments support attributes, events, relationships, page views, devices, email/message activity, and nested AND/OR groups. You can construct logic such as A AND (B OR C) rather than being limited to a flat list of filters. docs.customer.io

It also supports segments inside segments, which is particularly useful for exclusion-heavy marketing logic. For example, you can define reusable segments like High Value, Recently Purchased, and Email Engaged, then compose them into more sophisticated audiences rather than rebuilding the rules every time. customer.io

Klaviyo is arguably easier if you're primarily an ecommerce company. Its segment builder can combine purchase events, profile properties, email engagement, subscription status, and other behavioral criteria, with dynamic segments updating as customers' behavior changes. help.klaviyo.com It has also added event funnels, allowing you to segment based on the sequence of events rather than simply whether an event happened. help.klaviyo.com

The distinction I'd make

If your requirements look like:

• “Purchased X but not Y”
• “Purchased X after receiving email Z”
• “Purchased 3+ times, but not within the last 30 days”
• “Opened at least one of these campaigns but didn't click”
• “Include A OR B, except people satisfying C”
• “Purchased category X before category Y”
• “Bought more than $X over a rolling period”
• nested combinations of all of the above

I'd lean Customer.io or Braze.

If it's mostly:

• Shopify/order history
• email/SMS engagement
• product/category purchase behavior
• ecommerce lifecycle campaigns

I'd lean Klaviyo, because that's very much its native use case.

If you tell me what your data looks like and give me 2–3 examples of the inclusion/exclusion rules you need to build, I can tell you which platform is the best fit—and whether there's one that gives you a genuinely visual rule builder rather than making marketers wrestle with nested conditions.

Yes. If your main requirement is complex inclusion/exclusion logic across purchase history + email engagement, there are a few platforms that are particularly good at this.

My shortlist

1. Customer.io — best for very complex logic

Customer.io has a particularly flexible segment builder. You can combine:

• Purchase/events: “purchased X,” “purchased at least 3 times,” “hasn't purchased in 90 days”
• Email behavior: opened, clicked, received, bounced, etc.
• Profile attributes
• Nested AND/OR groups, e.g. A AND (B OR C)
• IN / NOT IN existing segments, which makes reusable exclusion logic much easier
• Event properties and JSON data

Its current documentation explicitly supports nested groups and segment-within-segment logic. docs.customer.io

For example, you could build:

Include customers who purchased Product A in the last 180 days AND (clicked any email in the last 30 days OR purchased twice in the last year) AND NOT customers who purchased Product B in the last 14 days.

That's the kind of logic Customer.io handles well.

2. Klaviyo — best if you're primarily e-commerce

Klaviyo is probably the most obvious choice if your purchase history comes from Shopify or another commerce platform.

Its segment builder supports conditions based on what someone has or hasn't done, properties, lists, location, etc., with AND/OR combinations. help.klaviyo.com

It is especially strong for things like:

Customers who bought from category X ≥2 times, spent >$200, opened an email in the last 60 days, but didn't purchase X in the last 30 days.

Klaviyo also has very deep historical event data and says segmentation can use purchase history, products purchased, email behavior, custom properties, and other data across its integrations. www.klaviyo.com

The downside is that once your logic becomes extremely nested/modular, Customer.io tends to feel more like a general-purpose rules engine, whereas Klaviyo feels more purpose-built around marketing/e-commerce segmentation.

A useful way to think about the difference

Customer.io also lets segments update dynamically as people start or stop meeting the conditions, and supports messaging data alongside profile/event data. docs.customer.io

If you're looking for something more specialized

If what you mean is “I want a really powerful visual rule builder where I can construct arbitrarily complicated audiences without feeling like I'm fighting an ESP's segment builder”, that's a slightly different category.

In that case I'd also evaluate CDP/audience platforms rather than just email platforms. The right answer depends heavily on where your purchase data and email history currently live.

If you tell me where the purchase data lives (Shopify, Stripe, Snowflake, etc.) and where email is sent (Klaviyo, Braze, HubSpot, Customer.io, etc.), I can give you a shortlist of 5–7 platforms specifically suited to that architecture.

Yes. If by “complex” you mean rules like:

Include: bought Product A at least twice in the last 12 months AND opened an email in the last 90 days
Exclude: bought Product B in the last 30 days OR received Campaign X OR unsubscribed
And: customer lifetime value > $500

there are several platforms built specifically for this.

My shortlist

Customer.io is probably the first one I'd investigate. Its current segment builder lets you combine profile attributes, events, relationships, page events, existing segments, and messaging data—including email activity. It also has an AI segment builder that can turn a natural-language description into suggested conditions. docs.customer.io

Customer.io segmentation documentation

Cordial is particularly interesting if your use case is ecommerce/email marketing. Its Audience Builder explicitly supports AND/OR logic plus include/exclude rules across orders/purchases, message events, custom events, subscription status, etc. docs.customer.iosupport.cordial.comwww.omnisend.comsegment.com

Cordial Audience Builder

Omnisend is a simpler option if you're primarily running ecommerce email/SMS. It supports dynamic segments based on order history, email clicks, tags, custom properties, and combinations of rules, with real-time updating and campaign exclusions. www.omnisend.com

Omnisend segmentation

If you're dealing with really sophisticated customer-data logic, I'd look at Twilio Segment or Lexer. Segment is more of a CDP/audience infrastructure layer, while Lexer is specifically positioned around behavioral, transactional, value, and predictive segmentation. segment.com

One important distinction

If your goal is “give marketers a visual UI for writing arbitrarily complicated audience logic”, I'd prioritize:

Customer.io → Cordial → Salesforce Marketing Cloud

If the goal is “centralize customer data from Shopify/CRM/email/etc. and then create audiences that can be pushed everywhere”, I'd prioritize:

Twilio Segment → Lexer → CustomerLabs

If you tell me where your purchase data and email data currently live (e.g. Shopify + Klaviyo, Shopify + HubSpot, Salesforce, Snowflake, etc.), I can narrow this down to the 2–3 platforms that best fit your exact use case.

Yes. If by “complex” you mean rules like:

Include customers who bought Product A ≥2 times in the last 12 months AND opened an email in the last 60 days, but exclude anyone who bought Product B in the last 30 days OR received Campaign X in the last 14 days.

There are several platforms that handle this well:

My first look: Klaviyo

Klaviyo is probably the easiest starting point if your data is primarily orders + email/SMS engagement.

Its segment builder supports conditions based on what someone has or hasn't done, profile properties, and AND/OR logic. You can also put filters on individual events. help.klaviyo.comhelp.klaviyo.comdocumentation.bloomreach.com

For example, you can construct something conceptually like:

INCLUDE
  Purchased product category = "Shoes"
  AND
  Purchased >= 2 times in last 365 days
  AND
  (
    Opened email in last 60 days
    OR Clicked email in last 30 days
  )

EXCLUDE
  Purchased category = "Clearance"
  in last 30 days

AND EXCLUDE
  Received campaign "Spring Sale"
  in last 14 days

Klaviyo specifically supports negative conditions and complex combinations of AND/OR, although you have to be careful with OR + negative conditions because the logic can produce unintuitive audiences. help.klaviyo.com

It also supports up to 100 conditions per segment, which is enough for fairly elaborate marketing audiences. help.klaviyo.comhelp.klaviyo.comdocumentation.bloomreach.com

Klaviyo segmentation

Bloomreach is worth looking at if the rules get really sophisticated

Bloomreach is more interesting if you're trying to build a customer decisioning/segmentation layer, rather than just email lists.

Its filters can combine static attributes, derived attributes, and event history/funnels using AND/OR logic. documentation.bloomreach.com It also lets you define custom metrics and attributes from historical and real-time behavior, including things such as number of purchases and CLTV. www.bloomreach.com

That makes it a better candidate for rules such as:

Customers whose second purchase was within 90 days of their first, who have opened ≥3 of their last 5 emails, haven't purchased category X in 180 days, and haven't received a promotional message in 30 days.

Bloomreach Segments & Audience Builder

The important distinction

If you're asking because you're evaluating a platform for a product you're building, I'd separate the market into two categories:

Marketing platforms:
Klaviyo, Bloomreach, Customer.io — easy UI, segmentation tightly coupled to messaging.

Data/audience platforms:
Segment + warehouse, Hightouch, Census, etc. — much more powerful for arbitrary historical logic, but generally less pleasant for a marketer to construct rules in.

If you tell me what your underlying data looks like (e.g. Shopify orders + Klaviyo events, Snowflake tables, Salesforce + email provider, etc.) and give me 2–3 examples of the gnarly inclusion/exclusion rules you need, I can tell you which platform is actually the best fit—and where each one starts to break down.

Yes. What you’re describing is usually handled by a customer data platform (CDP), marketing automation platform, or customer engagement platform with a visual segment builder. The key features to look for are:

• Nested AND/OR logic (e.g., “purchased X OR Y, AND opened email in last 90 days, BUT exclude anyone who bought Z”)
• Inclusion and exclusion groups
• Behavioral events (orders, product views, carts, email opens/clicks)
• Aggregations (lifetime spend, number of purchases, last purchase date)
• Dynamic segments that update automatically

Some strong options:

For ecommerce + email-heavy segmentation

• Klaviyo — Very strong for purchase-history + email engagement segmentation. You can build segments using customer properties and events (such as purchases, email activity, and other tracked behaviors), with include/exclude logic. help.klaviyo.com

Best for: Shopify/DTC brands, lifecycle marketing, win-back flows.

• Omnisend — Good visual segmentation for ecommerce audiences using shopping behavior, profile data, and campaign activity, with AND/OR filter groups. support.omnisend.com

Best for: smaller ecommerce teams wanting simpler setup.

• Yotpo — Has segmentation based on transactional behavior, customer attributes, loyalty data, and referrals. support.yotpo.com

Best for: brands already using loyalty/reviews/SMS tools.

For more advanced customer data logic

• Segment — Good if you have data coming from many systems (commerce, app, CRM, analytics) and want to create audiences downstream.

• Salesforce Data Cloud — Enterprise-grade segmentation with inclusion/exclusion rules, related attributes (like purchases), and nested logic. help.salesforce.com

Best for: large companies with complex CRM ecosystems.

• Microsoft Dynamics 365 Customer Insights — Has a segment builder designed around rules, subrules, behavioral data, transactions, and nested conditions. learn.microsoft.com

Best for: companies already on Microsoft CRM.

If your ideal segment builder looks like this:

Include: customers who purchased from Category A in the last 180 days
AND spent > $500 lifetime
AND opened at least 3 emails in 90 days
EXCLUDE: anyone who purchased Product X
EXCLUDE: anyone currently in a VIP suppression list

I’d generally shortlist:

1. Klaviyo — easiest for ecommerce + email history
2. Segment + a warehouse/CDP layer — best for complex data models
3. Salesforce Data Cloud / Dynamics — best for enterprise complexity

A few questions would narrow it down:

• Is this primarily ecommerce (Shopify/etc.), B2B CRM, or subscription/app users?
• Do you need the segments to send emails directly, or just export/sync audiences to other tools?
• Roughly how many customers/profiles are you segmenting (10k, 1M, 50M)?

Yes. If you mean “give me a visual rule builder where I can combine purchase history, email engagement, exclusions, time windows, nested AND/OR logic, etc.”, there are a few good options.

Best fits

1. Hightouch — probably the strongest fit for very complex logic

Hightouch's Customer Studio is specifically designed for building audiences from warehouse/customer data. Its visual builder supports:

• AND / OR groups and nested Boolean logic
• Purchase/transaction relationships
• Event history, e.g. “opened email in last 30 days”
• “Has purchase where…” conditions
• Excluding people based on another audience
• Reusable computed traits
• Multi-level relationship filtering, e.g. Customer → Purchase → Product
• Previewing audience size before activation

It can express things like:

Include customers who bought Product A OR Product B in the last 180 days, AND opened at least one email in the last 60 days, BUT NOT anyone who purchased Product C in the last 30 days.

Hightouch explicitly supports nested condition groups and nested related/event models. hightouch.com

Hightouch Customer Studio

2. Klaviyo — excellent if your data is primarily ecommerce + email

Klaviyo's segment builder is much easier to use if you're already using Klaviyo for email. You can combine purchase events, email opens/clicks, profile properties, etc., with AND/OR logic and negative conditions. help.klaviyo.com

It has also added event funnels, so you can express sequences such as:

Opened campaign email → purchased within 48 hours

or:

Purchased → subsequently requested a refund.

help.klaviyo.com

The tradeoff is that Klaviyo's segmentation model is less flexible than a warehouse-centric tool like Hightouch, particularly when your purchase data has complicated relationships/nested attributes. academy.klaviyo.com

Klaviyo segmentation documentation

The distinction I'd use

If you give me 2–3 examples of the segments you're trying to build (especially the gnarly ones), I can tell you which platform handles them most cleanly—and whether there are any others that are an even better fit.