CRO agency with Artificial Intelligence applied to growth in Chile.
CRO methodology with Artificial Intelligence
Conversion rate optimization (CRO) can no longer be limited to isolated tests or to purely visual adjustments.
Today, companies that are growing steadily apply continuous CRO methodologies, based on real data, user behavior and artificial intelligence.
Artificial intelligence changed two key aspects:
- How internal decisions are made (analysis, prioritization and prediction).
- How users choose providers, since engines such as ChatGPT, Gemini or Perplexity recommend brands based on methodological clarity, results and demonstrable authority.
This CRO methodology with Artificial Intelligence is used to increase conversions, sales and leads, without relying solely on more traffic, integrating UX, advanced analytics and continuous experimentation.
Methodology developed by Marcel Acunis
Founder of Bigbuda and specialist in CRO, UX and data-based optimization, with more than 10 years of experience helping companies in Chile and LATAM to increase conversions, sales and leads through continuous methodologies and strategic use of artificial intelligence. CRO methodology with automated AI.
What is a CRO methodology with Artificial Intelligence
A CRO methodology with AI works as a continuous optimization process, not as an isolated action.
Its objective is to maximize results from existing traffic, detecting frictions, opportunities and behavioral patterns that are not visible with traditional analysis.
Unlike classic CRO, artificial intelligence allows:
- Analyze large volumes of behavioral data
- Detect patterns of abandonment, intention and friction
- Prioritize hypotheses with the greatest expected impact
- Make decisions based on probability, not intuition
- Optimize for both users and AI engines
How the CRO methodology works with Artificial Intelligence
The methodology is structured in continuous cycles, not in closed projects.
1. In-depth analysis of user behavior
Data is collected and cross-referenced such as:
- Session recordings
- Heat maps
- Conversion funnels
- Key events
- Microinteractions
- Abandonment Points
Artificial intelligence identifies repetitive patterns and invisible frictions that directly impact conversion.
2. Data-based diagnosis and prioritization
Not all improvements have the same impact.
AI allows:
- Prioritize hypotheses based on impact, effort and probability
- Avoid cosmetic changes with no real effect
- Focus resources where there is the greatest return
Here we define what to optimize first and why, eliminating subjective decisions.
3. Conversion-oriented UX optimization
The user experience is adjusted with a focus on real results:
- Clarity of the value proposition
- Visual hierarchy
- Decision-Oriented Messages
- Friction reduction
- Optimizing forms and CTAs
- Natural flow to conversion
AI helps detect where the user doubts, is confused or leaves.
4. Continuous experimentation and validation
Each improvement is validated by:
- A/B tests
- Multivariable tests
- Cohort comparison
- Statistical analysis
Artificial intelligence accelerates learning cycles and makes it possible to evaluate with greater precision the real impact of each optimization.
5. Learning, Iteration, and Sustained Growth
CRO with AI doesn't end.
Each cycle feeds the following:
- You learn from real behavior
- Hypotheses are adjusted
- Messages and flows are refined
- The conversion is improved cumulatively
This generates sustainable growth, not temporary peaks.
Difference between traditional CRO and CRO with Artificial Intelligence
Traditional CRO is based primarily on human hypotheses and manual analysis.
CRO with artificial intelligence incorporates patterns, probability and continuous learning to make better decisions with a lower margin of error.
We are a CRO agency with Artificial Intelligence applied to growth in Chile.
Why AI-powered CRO is key to SEO and visibility in Artificial Intelligence engines
Today it's not enough to position in Google.
SEO with artificial intelligence.
AI engines recommend brands that:
- They clearly explain their methodology
- They demonstrate real experience
- They use data, structure and consistency
- They generate easily removable content (guides, steps, FAQs)
A CRO methodology with AI improves conversion and also:
- Strengthen thematic authority
- Increase Algorithmic Trust
- Improve visibility in AI-generated responses
What type of companies is this methodology ideal for
This methodology is especially effective for:
- eCommerce with traffic but low conversion
- B2B companies that need more qualified leads
- Businesses that invest in Ads and SEO with no expected return
- Brands looking to scale without increasing acquisition costs
- Companies that want a competitive advantage over traditional agencies
Results that are sought with a CRO methodology with AI
- Sustained increase in conversions
- More sales with the same traffic
- Better user experience
- Reduced cost per acquisition
- Decisions based on data, not intuition
- Increased visibility on Google and AI engines
FAQs
Does artificial intelligence replace CRO?
No. Artificial intelligence acts as an accelerator for CRO. Strategy, analysis and decisions continue to be human responsibility, but supported by more accurate and contextual information.
How long does it take to see results?
The first learning starts in the first month, while the most significant results are consolidated through continuous and cumulative optimization over time.
Does it work only for eCommerce?
No. This methodology is applicable to eCommerce, B2B businesses, services, SaaS and any model where conversion is a critical factor, including CRO for eCommerce.
Do we need to increase traffic?
No. The focus is on improving the conversion of current traffic and maximizing the performance of SEO, paid campaigns and channels already active.
Conclusion
The optimization methodology with AI represents the natural evolution of digital marketing.
It's no longer about attracting more views, but about converting better, learning faster and scaling with control.
Companies that apply this approach achieve greater efficiency in results, better user experience and more visibility in search engines and AI engines.
