by Trivas.aiYou signed up. Now what?
That gap between "created an account" and "actually using the thing" is where most SaaS tools quietly lose people. Trivas.ai onboarding is built to close that gap fast: connect your data, get dashboards live, train your team on Wingman, and start making decisions off real numbers instead of guesswork. Here's exactly what happens, step by step, and how long each part takes.
Onboarding isn't just clicking "create account" and getting a login screen. We define it as the full stretch from signup to the day you have a working dashboard you actually trust.
That covers three phases. First, connecting your data sources: Shopify or WooCommerce, your ad platforms, GA4. Second, configuring dashboards and reports so they match how your team actually looks at the business. Third, training your team on Wingman AI so the insights layer isn't just sitting there unused.
Most brands are looking at live data within 3-5 business days. The range depends mostly on how many integrations you're connecting and whether any of them (looking at you, Amazon Seller Central) need extra approval time on the platform's end.
Start with your store. Shopify or WooCommerce connects first because it's the source of truth for revenue, orders, and customer data, everything else gets measured against it.
From there, ad platforms: Meta, Google Ads, TikTok, Amazon Ads. Most of these connect through OAuth, so you're just logging in and granting permission, no keys to copy and paste. A few older or more locked-down integrations still run on API keys, which takes a couple extra minutes but isn't complicated.
GA4 comes next, and this one matters more than people expect. Your funnel data from GA4 needs to be in place before attribution reporting is accurate. Skip it or connect it late, and your early attribution numbers will be off, not because the platform is wrong, but because it's missing a piece of the picture.
One thing worth flagging up front: if you're an Amazon seller connecting through Seller Central, budget extra time. Amazon runs its own verification on top of ours, and that can add 24-48 hours before the connection is fully live. It's not something we control, so plan around it rather than being surprised by it.
If you want the full technical rundown on how each integration handles auth and permissions, our data integration help docs walk through it channel by channel.
Once data's flowing, you're not starting from a blank canvas. The dashboards are Redshift-backed and come with pre-built templates for Amazon, Shopify, and ad spend reporting already configured. That's the starting point, not the finish line.
From there, a Trivas team member gets on a guided call with you to customize. This is where your existing KPI structure gets mapped in, whatever metrics your team already lives by, whatever format your weekly reporting takes. The goal is a dashboard that looks like it was built for your business, because it was.
Here's the part people don't expect: historical data backfill isn't just a nice-to-have, it's standard. We typically pull in 12-24 months of history during setup, not just data going forward from the day you connect. That means your first dashboard view already has trend lines, seasonality, and year-over-year comparisons, instead of a flat line that only starts to mean something three months from now.
Wingman doesn't need much to get started, but it does need a few things in place. Minimum data history, your connected channels, and some defined goals or benchmarks for your business. Without those, it's just guessing at what "normal" looks like for you.
Alert thresholds get set during onboarding, not bolted on later as an afterthought. If a CAC spike above a certain point should trigger a flag, or a ROAS drop on a specific channel needs eyes on it fast, you define that threshold up front. That way Wingman is already watching for the things that matter to your business from day one, instead of you having to go configure it after you've already missed something.
Forecasting works the same way. The more real inputs you give it early, seasonality patterns, historical spend, inventory data, the sharper the forecast is out of the gate. Brands that skip this step and just let forecasting run on bare-minimum data tend to get vaguer, less useful projections early on. It's worth the extra 15 minutes during setup.
Not everyone on your team needs the same view. A founder or CEO usually wants a high-level snapshot: revenue, profit, top-line trends. A marketing lead wants channel performance and campaign detail. A data analyst wants to get into the weeds. Role-based access sets each of these as the default view, so nobody's digging through irrelevant tabs to find the three numbers they actually check every day.
Training happens live, not through a pile of onboarding emails you'll never open. The session covers dashboard navigation, how to export reports for your own decks or meetings, and how to actually ask Wingman questions in plain language instead of building filters manually.
After that, you're not on your own. There's a help center and a data dictionary for when you need a refresher on how a specific metric is calculated, useful six weeks in when someone new joins the team and asks "wait, how is this number defined again?"
Integrations fail sometimes. Usually it's an API permission issue or an expired token, not something dramatic. These typically get resolved within a business day once flagged, and our team is the one chasing it down, not you.
If historical data looks off against your own spreadsheets, that's worth flagging immediately rather than assuming it'll sort itself out. Sometimes it's a date range mismatch, sometimes it's a currency or timezone setting. Either way, it gets checked and corrected, not just shrugged off.
Adding a new channel or data source later doesn't mean starting the whole process over. Bring on a new ad platform six months in, or add a second store, and it plugs into what's already built rather than requiring a full reset.
Here's the timeline in plain terms: data connections happen on day one, dashboards go live within a few days depending on integration count, and your full team is trained within the first week. That's Trivas.ai onboarding from start to finish, no drawn-out multi-week rollout, no waiting a month to see your first real dashboard.
If you haven't signed up yet, start a trial and see how fast your own data actually comes together. If you're already a customer and want a deeper look at what's included, the onboarding and training solution page breaks it down in more detail.
Either way, worth keeping an eye on our blog for more on getting the most out of your setup once you're in.
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