{"id":207183,"date":"2025-11-28T11:02:58","date_gmt":"2025-11-28T11:02:58","guid":{"rendered":"https:\/\/www.similarweb.com\/blog\/?p=207183"},"modified":"2025-11-30T12:08:02","modified_gmt":"2025-11-30T12:08:02","slug":"agentic-workflows","status":"publish","type":"post","link":"https:\/\/www.similarweb.com\/blog\/daas\/data-basics\/agentic-workflows\/","title":{"rendered":"What Are Agentic Workflows (And Why Businesses and Agencies Are Leaning In)"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Businesses don\u2019t just need chatbots. They need agents.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">There\u2019s a difference. <\/span><span style=\"font-weight: 400;\">Chatbots are reactive. They respond to questions in the moment. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Agents are proactive. They execute tasks, monitor changes, and make decisions over time.\u00a0<\/span><span style=\"font-weight: 400;\">More importantly, they can be role-defined, context-aware, and autonomous.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here\u2019s the shift:<\/span><\/p>\n<table>\n<tbody>\n<tr>\n<td><\/td>\n<td><b>Chatbot<\/b><\/td>\n<td><b>AI Agent<\/b><\/td>\n<\/tr>\n<tr>\n<td><b>Function<\/b><\/td>\n<td><span style=\"font-weight: 400;\">Answers questions<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Executes tasks and makes decisions<\/span><\/td>\n<\/tr>\n<tr>\n<td><b>Context<\/b><\/td>\n<td><span style=\"font-weight: 400;\">Short-term memory<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Maintains long-term goals and state<\/span><\/td>\n<\/tr>\n<tr>\n<td><b>Action<\/b><\/td>\n<td><span style=\"font-weight: 400;\">Generates summaries<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Pulls data, triggers workflows, and collaborates with other agents<\/span><\/td>\n<\/tr>\n<tr>\n<td><b>Autonomy<\/b><\/td>\n<td><span style=\"font-weight: 400;\">User-driven<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Self-directed, can schedule, alert, and act without prompting<\/span><\/td>\n<\/tr>\n<tr>\n<td><b>Example<\/b><\/td>\n<td><span style=\"font-weight: 400;\">\u201cShow me competitor traffic.\u201d<\/span><\/td>\n<td><span style=\"font-weight: 400;\">\u201cMonitor competitors and alert me when traffic spikes above baseline.\u201d<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><span style=\"font-weight: 400;\">What are agentic workflows?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Lets take this a step further.<\/span><\/p>\n<p>Agenting workflows or networks are systems of connected <a href=\"https:\/\/www.similarweb.com\/blog\/daas\/data-basics\/ai-agents\/\"><span style=\"font-weight: 400;\">AI agents<\/span><\/a><span style=\"font-weight: 400;\"> that work together toward a shared goal. Each agent has a defined role: one collects data, another interprets it, and another creates a report.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The real power begins here. In fact, <\/span><a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai\"><span style=\"font-weight: 400;\">recent data<\/span><\/a><span style=\"font-weight: 400;\"> shows that 23% of organisations are already scaling agent-like systems, and another 39 % are testing them.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Imagine a workflow where a:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Search Trends Agent<\/b><span style=\"font-weight: 400;\"> pulls external demand shifts.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Competitive Intelligence Agent<\/b><span style=\"font-weight: 400;\"> tracks site traffic and engagement from Similarweb.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Social Listening Agent<\/b><span style=\"font-weight: 400;\"> adds sentiment data from third-party sources.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Report Writer Agent<\/b><span style=\"font-weight: 400;\"> compiles the results into an executive summary.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">But in practice, getting those sources to work together has always been the hard part. Every platform structures data differently, and every API has its limits.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Stitching them into a single, coherent workflow requires time, custom code, and ongoing maintenance.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Many businesses are facing this challenge because it aligns with their existing work processes. They build processes. They manage multiple brands. They deal with high volumes of repeatable analysis. Agentic workflows are a way to scale that, without scaling headcount.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">And the <\/span><a href=\"https:\/\/www.similarweb.com\/corp\/ai\/mcp\/\"><span style=\"font-weight: 400;\">Similarweb MCP (Model Context Protocol) server<\/span><\/a><span style=\"font-weight: 400;\"> is what connects the dots.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Why Similarweb is a design partner, not just a data source<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">There\u2019s a fundamental shift brought about by the growing complexity of integrating multiple data sources into coherent agentic workflows and systems. Teams need help designing how those sources interact, complement each other, and produce consistent outcomes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is where MCP becomes more than an integration and more of a collaboration layer.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">It\u2019s why businesses are now focused less on the question, \u201cWhat metrics can you provide?\u201d and more on, \u201cWhat should our agents do with this data?\u201d<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Designing workflows and delivering data<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">MCP is built for this shift. It allows agencies to embed Similarweb insights into the logic of their AI workflows. The focus is on both building tools that report data and creating systems that drive action.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">That changes the conversation entirely. Agencies are designing agents that continuously monitor shifts, run analyses, and generate outputs without requiring human intervention.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Similarweb becomes part of the workflow, not a separate step.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you\u2019re building an agentic workflow. Then you\u2019re looking for input on where digital behavior matters most, what signals to track, and how to define meaningful outcomes.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These are design-level decisions, and Similarweb can help shape them from the inside out.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Governance isn\u2019t optional anymore<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">As agentic systems scale across teams and clients, consistency becomes a strategic requirement. So you want systems you can trust, where logic and data aren\u2019t dependent on the quality of someone\u2019s prompt.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">MCP gives them that control. It enables teams to:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pre-instruct agents on how to analyze or interpret data<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Define which data sources are used, and when<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Apply permissions or guardrails to ensure compliant outputs<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">This is how agencies ensure their agentic systems remain reliable, scalable, and safe.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Orchestrating workflows of intelligence<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">If there\u2019s one early misstep we\u2019ve spotted businesses making with our tech, it&#8217;s building a single \u201cSimilarweb agent\u201d that answers traffic questions. Sure, it may work, it may be useful, but it barely scratches the surface of what you can do.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The real opportunity is orchestration.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">We\u2019ve seen a trend to deploy workflows of agents, each with a defined role: one monitors competitors, another tracks keyword trends, and another generates weekly summaries. These agents collaborate and exchange insights while operating autonomously.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this model, Similarweb connects the system, linking agents, data, and outcomes through its MCP server.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">What agentic workflows look like in the real world<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The shift from dashboards to intelligent workflows is happening now, across teams deploying Similarweb MCP in real-world environments.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">From manual effort to autonomous systems<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">One company, for example, had spent six months manually building a composite scorecard to benchmark brand performance. The project was delayed, resource-intensive, and difficult to scale.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Once they adopted <\/span><a href=\"https:\/\/developers.similarweb.com\/docs\/claude-mcp-integration\"><span style=\"font-weight: 400;\">Similarweb\u2019s MCP with Claude<\/span><\/a><span style=\"font-weight: 400;\">, that same process was automated in a single day. The agent pulled the right metrics, applied custom weightings, and generated an executive-ready summary, instantly.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Another used MCP to build a monthly performance dashboard that tracks SERP performance, Gen AI traffic, and keyword trends.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In some cases, teams even use Similarweb\u2019s <\/span><a href=\"https:\/\/www.similarweb.com\/corp\/ai\/data-for-ai\/\"><span style=\"font-weight: 400;\">data for AI training<\/span><\/a><span style=\"font-weight: 400;\">, feeding Similarweb insights into foundation models to improve how agents understand market trends or digital behavior.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This used to take hours each month across multiple platforms. Now, one conversational prompt triggers a full report, custom-branded, insight-rich, and delivered in minutes.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Faster answers, broader adoption, easy access to data<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Then there\u2019s the company that embedded Similarweb into its internal chatbot. Now, any team member can access insights via natural language without leaving their existing tools.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The result? Faster answers, broader adoption, and more intelligent client conversations.<\/span><\/p>\n<p><img decoding=\"async\" class=\"alignnone wp-image-207189 size-full\" src=\"https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2025\/11\/attachment-agentic-workflow.png\" alt=\"Agentic workflow example\" width=\"1920\" height=\"1200\" srcset=\"https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2025\/11\/attachment-agentic-workflow.png 1920w, https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2025\/11\/attachment-agentic-workflow-300x188.png 300w, https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2025\/11\/attachment-agentic-workflow-1024x640.png 1024w, https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2025\/11\/attachment-agentic-workflow-768x480.png 768w, https:\/\/www.similarweb.com\/blog\/wp-content\/uploads\/2025\/11\/attachment-agentic-workflow-1536x960.png 1536w\" sizes=\"(max-width: 1920px) 100vw, 1920px\" \/><\/p>\n<p><span style=\"font-weight: 400;\">What unites these examples is structure, as well as speed and automation. Each one shows how MCP allows Similarweb data to play a defined role within a broader agentic network.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These systems are quickly becoming <\/span><a href=\"https:\/\/www.similarweb.com\/blog\/daas\/data-basics\/ai-teammates\/\"><span style=\"font-weight: 400;\">AI teammates<\/span><\/a><span style=\"font-weight: 400;\"> &#8211; agents that don\u2019t just deliver data but actively collaborate with human teams to drive insights and action, supporting everything from reporting to strategic insight to action triggers.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is the future of agentic intelligence: not just surfacing information, but orchestrating it across roles, clients, and systems.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">FAQs<\/span><\/h2>\n<p><b>How are agentic workflows different from AI automation tools?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Traditional automation tools follow fixed rules and workflows. Agentic workflows, by contrast, use AI agents that can reason, make contextual decisions, and adapt based on changing inputs. They combine automation with intelligence, making them useful for complex, evolving tasks like market monitoring or insight generation.<\/span><\/p>\n<p><b>What types of business workflows benefit most from agentic workflows?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Agentic workflows are especially effective in workflows that involve repetitive analysis, multi-source data integration, or ongoing monitoring, such as <\/span><a href=\"https:\/\/www.similarweb.com\/blog\/marketing\/marketing-strategy\/competitive-intelligence\/\"><span style=\"font-weight: 400;\">competitive intelligence<\/span><\/a><span style=\"font-weight: 400;\">, <\/span><a href=\"https:\/\/www.similarweb.com\/blog\/research\/market-research\/what-is-market-research\/\"><span style=\"font-weight: 400;\">market research<\/span><\/a><span style=\"font-weight: 400;\">, <\/span><a href=\"https:\/\/www.similarweb.com\/corp\/custom-performance-reporting\/brand-health\/\"><span style=\"font-weight: 400;\">brand tracking<\/span><\/a><span style=\"font-weight: 400;\">, or campaign reporting. They reduce manual effort while improving consistency and response time.<\/span><\/p>\n<p><b>How does Similarweb\u2019s MCP fit into an agentic network?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">MCP acts as a coordination layer that connects Similarweb\u2019s data with AI systems. It helps agents access metrics, interpret them in context, and trigger actions without manual setup. This allows organizations to move from using Similarweb as a reporting tool to embedding it directly into their operational logic.<\/span><\/p>\n<p><b>Can agentic workflows use multiple data providers?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Yes. A robust agentic network can integrate insights from different sources, such as Similarweb data, CRM systems, and social listening platforms, to create a unified understanding of performance and behavior. MCP supports this by standardizing how agents access and use those data streams.<\/span><\/p>\n<p><b>What role does governance play in agentic workflows?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Governance ensures that AI agents use data responsibly and consistently. It defines which sources are trusted, how data should be interpreted, and what actions agents are allowed to take. MCP gives organizations a way to set these rules clearly, improving both compliance and output quality.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Businesses don\u2019t just need chatbots. They need agents.\u00a0 There\u2019s a difference. Chatbots are reactive. They respond to questions in the moment. Agents are proactive. They execute tasks, monitor changes, and make decisions over time.\u00a0More importantly, they can be role-defined, context-aware, and autonomous. Here\u2019s the shift: Chatbot AI Agent Function Answers questions Executes tasks and makes [&hellip;]<\/p>\n","protected":false},"author":524,"featured_media":207188,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[8500,8502],"tags":[],"class_list":["post-207183","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-daas","category-data-basics"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>What Are Agentic Workflows | Similarweb<\/title>\n<meta name=\"description\" content=\"Discover why businesses are moving beyond chatbots to autonomous Agentic workflows for task execution, decision-making, and scaled, multi-agent\" \/>\n<meta name=\"robots\" content=\"max-snippet:-1, max-image-preview:large, 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