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What is Ryan Swanstrom?
Ryan Swanstrom is a personal professional site for Ryan Swanstrom, a data leader and content creator. The site frames his work around using analytics to drive business strategy: finding the right data, choosing KPIs that move a business forward, and starting with the business problem before technology choices.
It is not a software product or a company. It functions as a hub for his writing and content, which the site says can also be found on his LinkedIn page and elsewhere online.
Who it is for
- Data and analytics professionals who want practical perspectives on leadership and strategy
- Business or product people who need to connect metrics to decisions
- Anyone looking for a data leader's published content in one place
How to use it
If you want a quick sense of his thinking, start with the blog and the "About the blog" section. If you are evaluating whether his approach fits your situation, look for posts that match your problem type: KPI selection, analytics strategy, or technology decisions. As a general practice, when following any practitioner's content, check whether their examples resemble your industry, data maturity and team size before applying their advice directly.
How does Ryan Swanstrom use analytics to drive business strategy?
Ryan Swanstrom frames analytics as a means to an end: business strategy comes first, and the data and tools serve it. On his site he describes his focus as finding the right data and analytics to identify KPIs that move the business forward, and he notes that technology choices should follow from the business problem rather than lead it.
That ordering matters in practice. Instead of starting with a dashboard or platform, the approach starts with the decision the business needs to make, then works backward to the metric and the data required to support it.
H3 Practical example A subscription company wants to reduce churn. A tool-first approach buys a visualization platform and reports every available metric. A strategy-first approach defines the decision — which customer segments to intervene in and when — then selects a small set of leading indicators, such as usage decline or support-ticket patterns, that predict churn early enough to act.
H3 When this approach fits
- You have more data than clear priorities.
- Stakeholders disagree about which numbers matter.
- Reporting effort is high but decisions are unchanged.
H3 Trade-offs
- Strategy-first work is slower to start and requires access to decision-makers, not just analysts.
- Narrow KPI sets can miss emerging signals, so they need periodic review.
- Tooling still matters at scale; the point is sequencing, not dismissing technology.
As a next step, write down the single decision your team faces this quarter and the metric that would change it. If you cannot name both, that gap is where the analytics work should begin.
For broader context on the field, see KDnuggets and O'Reilly.
What content does Ryan Swanstrom create and where can it be found?
Ryan Swanstrom creates content about using data and analytics to drive business strategy, with an emphasis on choosing the right metrics and starting from the business problem before picking technology. The site describes him as a data leader and content creator, and notes that his material appears on his own website as well as on LinkedIn and other places across the internet.
H3 Practical takeaway If you are a data analyst, manager or business stakeholder looking for a practitioner's view on KPIs and analytics strategy, start with his website and LinkedIn presence, then follow the links he shares to other platforms. The trade-off is that his content is spread across multiple channels, so you may need to check a few places to get the full picture.
How can I apply Ryan Swanstrom's approach to finding KPIs for my own business?
Start with the business problem, not the metric. Ryan Swanstrom's page frames analytics as useful only when it is "the right data and analytics" tied to driving business strategy — and he explicitly says that although technology choice matters, you should "always start with the business problem." So the practical sequence is: name the decision you're trying to improve, then pick the KPI that tells you whether that decision is working.
A concrete way to run it
- Write down one decision a manager actually makes this quarter (pricing, hiring, ad spend, retention outreach).
- Ask what would change that decision. If no number would change it, it isn't a KPI — it's trivia.
- Choose the smallest set of measures that capture it: one outcome measure plus one or two inputs you can influence.
- Set a baseline and a target from your own history, not from an industry benchmark.
- Review on a fixed cadence, and retire any KPI nobody has acted on in two cycles.
Example
A subscription business wants "more analytics." Reframed as a business problem: should we spend more on onboarding emails or on win-back campaigns? The KPI becomes trial-to-paid conversion rate by acquisition channel, with email engagement as the input measure. That's a number that changes a budget decision — which is the test Swanstrom's framing implies.
Where the trade-off sits
Broad dashboards feel safer because they cover everything, but they usually produce no decision. Narrow KPI sets force a choice and can miss emerging problems, so keep a small separate watchlist of health metrics that you monitor but don't optimize against.
If you want more of Swanstrom's own writing on this, his content is collected on his site Ryan Swanstrom and on his LinkedIn page. For general KPI design practice, the balanced-scorecard and OKR literature covers the same "start from the objective" logic.
What is Ryan Swanstrom's perspective on choosing technology for analytics projects?
Ryan Swanstrom's stated perspective is that technology should not lead the project: "Although the technology choice can be important, always start with the business problem." In other words, pick the tool after you understand the decision you are trying to improve, not before.
That view shows up alongside his emphasis on finding KPIs that "drive the business forward," and on analytics being "more than just data and analytics" — it has to be the right data and analytics. So the sequence he describes is: business problem → relevant KPIs → data and analysis → technology.
What this means in practice
- A team choosing a new BI platform would first write down the business question and the decision it informs, then evaluate whether existing tools can answer it before buying anything.
- A data engineer evaluating a new warehouse or pipeline tool would ask whether the current bottleneck is actually technical, or whether the problem is unclear metrics and definitions.
- A leader under vendor pressure to adopt the newest stack could use this as a tiebreaker: if the tool does not map to a named business problem, the choice is premature.
Where the trade-off sits
Starting with the business problem reduces the risk of expensive tools that nobody uses, but it can slow adoption when a technology genuinely unlocks questions you could not previously ask. The practical middle ground is to let the business problem set the requirements, then let those requirements — not familiarity or hype — decide the tool.
Next step: Before your next analytics tool decision, write one sentence naming the business decision it should improve and the KPI it should move. If you cannot fill that sentence, the technology question is not ready to answer yet.
For more of his writing on this and related topics, see Ryan Swanstrom.
How can I follow or connect with Ryan Swanstrom on LinkedIn?
Ryan Swanstrom's own site lists his LinkedIn page as one of the places his content appears, alongside the blog itself and "various other spots across the internet." The site does not publish a LinkedIn URL, so the practical route is to search LinkedIn by name rather than rely on a link from the site.
How to find and follow him
- Open LinkedIn and search for "Ryan Swanstrom." His profile identifies him as a data leader and content creator, which matches the description on Ryan Swanstrom.
- To follow without connecting, use the Follow button on his profile; it surfaces his posts in your feed without sending an invitation.
- To connect, use Connect with a short note. Mention a specific piece of his writing or a shared interest in analytics rather than sending a blank request.
- If you want his articles rather than his LinkedIn activity, the blog is the better subscription point; LinkedIn mainly carries shorter posts and shares.
A useful next step
Decide what you want from the connection before you send anything. If you are hiring or comparing notes on analytics leadership, a connection request with context makes sense. If you only want to read his posts, following is enough and creates less obligation on both sides. Either way, engage with something he has written first — a comment on a post or a question about an article gives the request a reason to exist.
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