decocms.com

What is deco?

deco is a service that operates and improves a company's digital experience — its website, app and storefront — using senior engineers plus AI agents. Its distinctive pitch is commercial rather than purely technical: the company says it charges based on the results it generates, not just for hours or licences. Its own software is described as open source and under the client's governance, so the client keeps control of the stack rather than handing everything to a closed vendor.

What deco actually does

The work spans a broad operational remit rather than a single tool:

• Auditing — reviewing site, app and storefront, and prioritising fixes by revenue impact.
• Implementation — headless storefronts, native commerce apps, and a sales concierge (an AI seller that chats, recommends and converts).
• Ongoing operation — a dedicated team sustaining and evolving the experience, plus integrations with ERP, OMS, CRM and payments.
• Growth and visibility — A/B testing in production, SEO and visibility in AI-generated answers, web analytics, Core Web Vitals performance, and 24/7 monitoring of errors and funnels.
• Automation — agents that take over repetitive work and run unattended.

Who it suits

The framing targets "people who take digital seriously" — brands with meaningful online revenue where a percentage improvement is worth real money. The page cites a Farm Rio case: an agent operating the product experience, measured by production A/B testing, with +10% revenue in key categories, operated by an agent plus deco engineers. That is deco's own reported figure, not an independent benchmark; treat it as a vendor case study and ask to see the test design, sample and duration before assuming similar results for you.

How it differs from alternatives

A practical next step: before any conversation, write down the one metric you'd be willing to pay against — incremental revenue in a named category, conversion rate on a named funnel, or Core Web Vitals thresholds — plus how it will be measured and who controls the test. That single document determines whether a results-based model helps you or becomes a negotiation. You can see how deco frames its own offering at deco.

How does deco's pay-for-results pricing model work?

deco's model, as described on its site, is outcome-based rather than a conventional software subscription: senior engineers and AI agents operate your site, app, and storefront, and you pay for the results produced. The clearest example given is a Farm Rio case in which an agent ran the product experience and was measured by an A/B test in production, with the company reporting +10% revenue in key categories and stating that the work was paid for through incremental revenue.

How the pieces fit together

Because the page ties payment to results, the practical starting point is agreeing on what counts as a result and how it will be measured. The site lists a pricing page, so exact commercial terms should be confirmed there rather than assumed from the marketing description. If you want to evaluate this model, compare it with alternatives such as Shopify for a standard commerce platform, Vercel for hosting and frontend delivery, or Optimizely if experimentation tooling is your main need. The deciding question is whether you have a measurable revenue or conversion metric, sufficient traffic to test it, and a willingness to let an external team operate part of your digital experience.

How can I start using deco for my e-commerce site?

Start by treating deco as an operating partner rather than a tool you install alone. The site positions its offer around senior engineers, AI agents and proprietary open-source software running your site, app and storefront under your governance, with payment tied to results. The practical first step is to pick one entry point instead of trying to fix everything at once.

Likely starting paths

• Experience auditing — an audit of site, app and storefront, prioritised by revenue. This suits stores that know something is underperforming but lack a clear order of attack.
• Headless storefront implementation — high-volume storefronts launched in weeks, aimed at brands replatforming or outgrowing a template.
• Native commerce app — for teams whose mobile experience is a bottleneck.
• Sales concierge — an AI seller that chats, recommends and converts, useful when product discovery is the weak link.
• Ongoing operation — a dedicated team sustaining and improving the experience, plus integrations for ERP, OMS, CRM and payments.

What to prepare before contacting them

A revenue-prioritised list of problems, access to analytics and storefront code, and a defined success metric. The Farm Rio case on the page is presented as an agent operating product experience, measured by A/B testing in production, with a reported 10% revenue lift in key categories and payment based on incremental revenue. Treat that as their published case study, not a guarantee for your store.

How to choose

If your conversion rate is the issue, auditing or CRO testing is the natural entry. If your platform limits you, headless storefront work comes first. If discovery and merchandising stall shoppers, the sales concierge is the more direct lever.

A good next step: open deco and start the free monitoring option mentioned on the page, then use what it surfaces to decide which service to begin with.

What results have brands like Farm Rio achieved with deco's AI agents?

Farm Rio grew key-category revenue by 10% using a deco AI agent, according to deco's own impact study. The company says the result was measured with an A/B test in production, with the agent working alongside deco engineers, and that its fee was tied to the incremental revenue generated.

That is a single, vendor-reported case, so treat the 10% as an indicative rather than guaranteed outcome. The useful detail is the method: a live split test on real traffic, focused on product experience in specific categories, rather than a sitewide redesign. That setup is what makes the number worth paying attention to, because it isolates the agent's contribution instead of crediting a broader relaunch.

What this means if you are evaluating deco

• Best fit: ecommerce brands with enough traffic to run a credible A/B test and enough revenue at stake to justify a results-based contract.
• Weaker fit: early-stage stores with low traffic, where a 10% lift would be hard to detect or hard to fund.
• The claim to verify in your own case: whether the agent can move your key categories, and how "incremental revenue" is defined and measured before you sign.

Practical next step

Ask deco for the Farm Rio case write-up and check three things: which categories were tested, how long the test ran, and how the incremental-revenue fee was calculated. Then ask what a comparable test would look like on your catalog — which pages, which traffic split, and what minimum detectable lift your current volume supports.

For broader context on how brands structure this kind of work, you can compare approaches with Shopify or commercetools if you are weighing headless storefront options alongside an operating partner.

Does deco's software support ERP, CRM, and payment integrations?

Yes. deco lists Integrations as one of its services, covering ERP, OMS, CRM and payments — described as connecting these systems to the site, app and storefront it operates. The page positions this alongside ongoing operation work rather than as a standalone connector product.

H3 What the page actually says

• Integrations is an explicit service line: "ERP, OMS, CRM, pagamentos — tudo conectado."
• The offering is framed as a single team and a results-based contract, from auditing through automation, so integrations sit inside an operations engagement.
• deco also states its software is open source and runs under the client's governance, which matters if your IT team needs to inspect or extend connectors.

H3 What is not stated The page does not name specific ERP, CRM or payment vendors, nor does it confirm pre-built connectors versus custom work. Treat vendor-level compatibility as something to verify directly.

H3 Practical next step If you run a storefront with, say, an ERP for stock and a CRM for service tickets, ask deco three things before signing: which systems they have already integrated, who owns the connector code, and how failures are monitored. The observability and monitoring service they describe (24/7 error and funnel monitoring) is the natural place for integration failures to surface, so ask how those alerts reach your team.

For context on the platform itself, see deco. If you are comparing commerce platforms with strong integration ecosystems, Shopify and commercetools publish their own app and connector directories.

How does deco improve SEO and visibility in AI-generated answers?

deco addresses both classic search visibility and visibility inside AI-generated answers through a service it calls SEO / GEO / AEO — search engine optimization plus optimization for generative and answer engines. It also lists web analytics as a separate offering, which matters because AI-answer visibility is hard to improve without reliable event and query data.

What the page actually claims

• SEO / GEO / AEO is listed as a service: being visible in Google and in AI responses.
• Experience Auditing prioritizes site, app and storefront issues by revenue, so technical fixes are ranked by business impact rather than by checklist order.
• Performance work targets Core Web Vitals, which affect crawling, rendering and user experience.
• Web Analytics provides trustworthy data and clean events for decisions.
• Automation and Observability keep monitoring and repetitive work running continuously.
• A published impact study describes an AI agent operating product experience at Farm Rio, measured by A/B testing in production, with +10% revenue in key categories and payment tied to incremental revenue. That is deco's own case claim, not an independent audit.

How that translates into AI-answer visibility

AI answers are assembled from content that is crawlable, structured, fast and consistent across pages. In practice, the levers overlap heavily with technical SEO: clean rendering, stable URLs, accurate product and category data, schema markup, and content that directly answers buyer questions. deco's combination of auditing, headless storefronts, analytics and monitoring is a plausible way to keep those inputs healthy, because AI systems tend to cite pages that load reliably and state facts clearly.

The trade-off: this is an operations model, not a plugin. The page says deco operates sites and apps with senior engineers and AI agents, and that clients pay for results generated. That suits brands with enough traffic and revenue to justify an ongoing engagement, and less so a small site wanting a one-off fix.

A practical next step

If AI-answer visibility is your goal, start by testing what assistants currently say about your brand and top categories, then compare that against your crawlable content. deco's auditing service is positioned to prioritize exactly that gap by revenue. For context on how search and answer engines differ, see Google Search Central and Schema.org.