MarTech

Stop managing tools. Start running campaigns that convert.

We build campaign orchestration platforms, attribution engines, AI content tools, and customer analytics systems in 12 weeks. Software that makes your marketing team 3x more productive without adding headcount.

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20+

Martech products

85%

Traffic increase

28%

Conversion lift

Overview

Your marketing stack became the bottleneck

MarTech software development at RaftLabs focuses on the three areas that most directly move pipeline - attribution accuracy, content velocity, and segmentation precision. We bring patterns from 100+ products across adjacent industries to build multi-touch attribution engines, AI content platforms, predictive segmentation tools, and campaign orchestration systems - each engineered for measurable CAC reduction and conversion lift.

Marketing teams use an average of 12 tools. They spend more time moving data between platforms, building reports, and managing integrations than actually running campaigns. The stack that was supposed to drive growth became the bottleneck.

We build the connective tissue. Campaign orchestration that unifies channels. Attribution models that actually tell you which spend drives revenue. Content systems that produce on-brand assets in minutes instead of days.

Every product we ship cuts tool count, automates repetitive workflows, and gives marketing leadership the metrics they need to make confident budget decisions.

Experience Signal

20+ martech products shipped across SaaS companies, D2C brands, and multi-brand retailers - attribution engines, campaign platforms, AI content tools, and analytics systems. 12 weeks is our default, not our stretch goal.

20+

Martech products

85%

Traffic increase

Industry Pain Points

What's broken in martech

01

Marketing teams manage 10-15 disconnected tools and spend 30% of their time on data wrangling instead of strategy

02

Multi-touch attribution is a spreadsheet exercise - nobody trusts the numbers, so budget allocation runs on gut feel

03

Content production bottlenecks marketing velocity - every campaign waits for design and copy resources

04

Personalization requires engineering tickets that take weeks, so most customers see the same generic experience

05

Customer segmentation relies on static lists that are outdated by the time campaigns launch

06

CAC keeps rising because teams optimize channels in isolation without seeing the full conversion path

Solutions

Problems we solve in martech

Each solution is built from patterns we've validated across 100+ products. No experiments on your budget.

01

Campaign orchestration

Unified platform that plans, executes, and optimizes campaigns across email, paid, social, and web. AI adjusts send times, audiences, and creative based on real-time performance signals.

02

Multi-touch attribution engine

Connects ad platforms, CRM, and revenue data to build a unified attribution model. Shows which touchpoints drive pipeline and revenue - not just clicks. Marketing and finance trust the same numbers.

03

Content generation and optimization

Generates on-brand copy, email variations, ad creative, and social posts using your brand voice and past performance data. Built-in A/B testing at scale - test 20 variants instead of 2.

04

Predictive customer segmentation

AI segments customers by purchase propensity, lifetime value, churn risk, and engagement patterns. Segments update in real time as behavior shifts - no more stale lists.

05

Real-time web personalization

Personalizes website content, CTAs, and product recommendations based on visitor behavior, firmographic data, and intent signals. No engineering tickets - marketing controls the rules.

06

Marketing analytics and reporting automation

Pulls data from every tool into a single reporting layer. AI generates weekly performance summaries, flags anomalies, and recommends budget reallocation based on ROI trends.

Use Cases

Real-world use cases

Attribution engine for a B2B SaaS company

Problem

A $30M ARR SaaS company spent $4.2M annually on marketing but couldn't attribute pipeline to specific channels. The CMO made budget decisions using last-click data from Google Analytics.

What we built

We built a multi-touch attribution system connecting their ad platforms, HubSpot CRM, and Stripe revenue data - with data-driven attribution models crediting pipeline and revenue across all touchpoints.

Result

The team discovered LinkedIn drove 3.2x more pipeline per dollar than Google Ads. Budget reallocation cut CAC by 28% and grew marketing-sourced pipeline 41% in two quarters.

AI content platform for a D2C brand

Problem

A direct-to-consumer brand needed 200+ content assets per month across email, social, and web. Their 3-person content team was a bottleneck. Campaign launches delayed an average of 8 days.

What we built

We built an AI content platform trained on their brand voice, past campaigns, and product catalog. It generated email, social, and ad copy with automated A/B variant creation and performance-based optimization.

Result

Content production climbed 4x without adding staff. Campaign launch delays disappeared. Email open rates climbed 22% through AI-optimized subject lines and send-time personalization.

Campaign orchestration for a multi-brand retailer

Problem

A retailer with 4 brands managed campaigns separately in each brand's Mailchimp, Meta, and Google accounts. No cross-brand audience insights. Duplicate ad spend targeting the same customers.

What we built

We built a unified campaign orchestration platform with shared audience data, cross-brand suppression rules, and centralized performance reporting. Each brand kept creative control while sharing operational intelligence.

Result

$380K in duplicate ad spend eliminated annually. Cross-brand customer identification grew remarketing efficiency 35%. Campaign setup time dropped from 3 days to 4 hours.

Proof

How we've solved martech problems

MarTech

Conversational AI chatbot SaaS for Perceptional

Replaced static surveys with intelligent conversational bots - 4x deeper product insights, 48-hour time to useful data, concept to launch in 12 weeks.

12 weeks

Delivery timeline

4x deeper

Insight depth

“I spent years at Amazon fighting static surveys. RaftLabs built a working prototype in four days that already outperformed every survey tool I'd used. Twelve weeks later, we had a full SaaS that product teams actually want to use.”

Founder, Perceptional (ex-Amazon PM)
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MarTech

Loyalty Rewards app for Sanbra Fyffe (Instantor®)

Tiered loyalty rewards app for Ireland's plumbing and heating industry - 14 weeks to launch, 25% increase in average order value, 60% customer engagement boost.

14 weeks

Time to launch

100+ in month one

Receipt uploads

“We supply through merchants, so we never had a direct line to the plumbers using our products. The loyalty app changed that overnight - we now know who our most loyal installers are and can reward them directly.”

Sanbra Fyffe Marketing Team, Brand Marketing, Instantor®
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MarTech

Referral & viral marketing platform for GrowViral

Centralized referral, viral, and affiliate campaign management - embeddable campaign designer, real-time analytics, and automated rewards in 14 weeks.

3

Campaign types

14 weeks

Delivery timeline

“We were duct-taping together four different tools for referral and affiliate campaigns. GrowViral replaced all of them - our clients can now launch campaigns themselves without filing a support ticket.”

GrowViral Founder, CEO
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Our Approach

How we approach martech projects

1
Phase 1· Week 1-2

Marketing stack audit and metrics mapping

We audit your current tools, data flows, and reporting. Redundancies, data gaps, and the metrics that actually matter for your business model get identified.

Deliverables

  • Tool stack audit with redundancy and gap analysis
  • Data flow map showing where attribution breaks
  • Metrics framework tied to revenue outcomes, not vanity metrics
2
Phase 2· Week 2-4

Product design and data architecture

We design the product with your marketing team, not just your engineering team. Data architecture keeps attribution clean, segmentation real-time, and reporting reliable.

Deliverables

  • Product wireframes validated by marketing operators
  • Data architecture connecting all marketing and revenue sources
  • Integration specifications for ad platforms, CRM, and analytics
3
Phase 3· Week 4-10

Build, integrate, and validate

We build in sprints, integrating with your live marketing stack. Your team uses the product on real campaigns before launch to validate workflows and data accuracy.

Deliverables

  • Working product integrated with live marketing tools
  • Data validation report comparing new system to existing metrics
  • Marketing team feedback incorporated into final iteration
4
Phase 4· Week 10-12

Launch, training, and optimization

We launch with team training and documentation. Ongoing optimization uses performance data to improve AI models, attribution accuracy, and campaign recommendations.

Deliverables

  • Full launch with marketing team trained and self-sufficient
  • Performance baseline for continuous improvement tracking
  • Optimization playbook for the marketing team to run independently

Outcomes

Measurable outcomes

25-40% reduction in customer acquisition cost through better attribution and budget allocation
3-5x increase in content production velocity without adding headcount
30-50% reduction in campaign setup and launch time through automation
15-25% improvement in conversion rates through real-time personalization
Unified reporting that marketing and finance trust - one source of truth for ROI
3-5 redundant tools dropped from the marketing stack, cutting SaaS spend by $50K-$200K a year

Free Tools

Free tools for martech

Calculators and assessments built from real project data. No signup required.

See all free tools

Pattern Transfer

RaftLabs built predictive segmentation for an insurance risk scoring product before applying the same behavioral clustering approach to marketing audience segmentation. Both require grouping entities by behavioral patterns to predict future actions. Insurance predicts claims risk. Marketing predicts purchase intent. Same math, different labels.

Services

Services for martech

Frequently asked questions

Projects range from $50K-$200K. An attribution engine starts around $50K. A full campaign orchestration platform with AI content runs $120K-$200K. We define scope and pricing in a strategy session before work begins.

Next Step

Every dollar of CAC you can't attribute is a dollar you're probably wasting.

One call with a founder. No sales team, no follow-up sequence. If we can't help, we'll say so.

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