
Causiq
Marketers with insights and recommendations to help them do more with less.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor | €0.0 | round |
$100k | Seed | ||
Total Funding | 000k |
SEK | 2021 | 2022 | 2023 | 2024 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | 27 % | 337 % | (98 %) |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
% profit margin | (1852 %) | (1379 %) | (19 %) | (188 %) |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Company filings or news article
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Causiq, a marketing analytics company established in 2020, operates from its headquarters in Stockholm, Sweden. The firm was co-founded by Henrik Feldt and Lukas Snizek, who also serves as the CEO. Snizek, a self-described salesman by passion, previously founded QuickSpeech, a microlearning platform, demonstrating a background in applying technology to business processes. Feldt also contributes to the company's public-facing content through its blog.
The company targets the persistent challenge marketers face in demonstrating return on investment. Causiq offers a software-as-a-service (SaaS) platform that assists marketing teams in understanding the contribution of each marketing channel to revenue and conversions. Its client base ranges from marketing managers and media buyers to Chief Marketing Officers (CMOs), particularly within the e-commerce sector. The business model is centered on providing actionable insights to facilitate more effective budget allocation across all marketing channels.
Causiq's core product employs a modern approach to Marketing Mix Modeling (MMM), a statistical analysis technique used to estimate the impact of various marketing tactics on sales. The platform utilizes an AI-based experimentation engine and Bayesian principles, which allows its models to be self-learning and account for variables like seasonality and brand effects. A key differentiator is its ability to operate without relying on third-party cookies, making it resilient to tracking preventions and capable of analyzing both online and offline campaigns in a unified view. Data is ingested through automated connectors or manual uploads of aggregated, non-personal marketing data. Unlike traditional MMM tools that may update monthly or quarterly, Causiq provides daily results, enabling marketing teams to operate with greater agility. The platform delivers predictive analytics to forecast results and offers recommendations to optimize advertising spend. Keywords: marketing mix modeling, MMM, marketing analytics, ROI optimization, budget allocation, conversion tracking, e-commerce analytics, causal inference marketing, attribution modeling, ad spend optimization, marketing data science, cookieless attribution, predictive analytics, channel performance, Henrik Feldt, Lukas Snizek, Stockholm startup, marketing ROI, campaign analysis, cross-channel analytics, demand generation