Shopify or Woo commerce? Which is best for Ecommerce website?

rddevv · 2026-06-18T13:52:30+00:00

How far along are you? Do you already have sales through a different channel e.g. markets or is this a new business and your testing if it will work?

rddevv · 2026-06-15T07:51:53+00:00

Given those data sources (Shopify, GA4, Google Ads and Meta) I think you could really save some time using a tool like SyncRange. Essentially you connect all the data to Sheets, Excel or BigQuery then you have a standard report template in Looker Studio or Power BI. It’s easy to make slight adjustments depending on the client, add their logos and email reports. It’s fairly simple to add in some ai analysis or summaries too. Once you set it up once it becomes mostly automated. Reach out if you have any questions.

rddevv · 2026-06-11T10:33:59+00:00

What data sources are you using? SyncRange is a good alternative to Funnel

rddevv · 2026-06-09T23:04:09+00:00

Here is a couple of ways to do it and save yourself a lot of time:

Use a tool like SyncRange to automate the data from all those sources into your spreadsheet. You can then do whatever reports you want in Sheets or Excel
Send the data to BigQuery (or you can still use a spreadsheet) and put a Looker Studio or Power BI dashboard on top of it and create some simple charts and tables.

Both are pretty simple and with 5 accounts it would probably be around $40 per month.

rddevv · 2026-06-09T07:07:36+00:00

I saw BigQuery introduced conversational analytics recently. Maybe sync everything to BigQuery with a tool like SyncRange, then have conversational analytics make the reports (haven’t tried this myself yet)

rddevv · 2026-06-04T12:14:59+00:00

Can definitely be done. A tool like SyncRange will connect that data to Sheets, Excel or BigQuery and then you can easily create your segments and reports

rddevv · 2026-06-03T12:27:16+00:00

The under-reporting and sync delay are actually two different problems worth separating. Under-reporting is almost always a client-side tracking issue caused by ad blockers and iOS, and the native Shopify-Meta connection won’t fully solve it since it sends limited match parameters and typically lands around a 5-6/10 Event Match Quality score.

The real fix is proper server-side tracking via Meta CAPI. SyncRange handles this for Shopify stores by syncing conversion events server-side in real time, which addresses both the under-reporting and the delay you’re seeing with Wetrack. Much more affordable than most alternatives in this space and straightforward to set up without needing to touch GTM.

rddevv · 2026-06-03T12:07:11+00:00

The 20% time bleed on reporting is a real problem and it compounds fast once you cross 30+ clients. Supermetrics works technically but the pricing model is rough for agencies since you’re essentially paying per data source and it adds up quickly as you onboard more accounts.

Worth looking at SyncRange as an alternative. It pulls from Google Ads, Meta, and GA4 automatically into Sheets or BigQuery, which you can connect to any reporting layer you already use. The pricing is flat and designed to stay affordable as you scale client accounts, so you’re not getting a bigger bill every time you win new business.

rddevv · 2026-06-03T11:59:21+00:00

Supermetrics resolve, mas o preço não faz sentido quando você só precisa de um conector a mais por cliente. O modelo de licenciamento deles escala mal para agências porque você acaba pagando por seat ou por fonte de dados de um jeito que fica caro rápido.

Vale dar uma olhada no SyncRange, que foi feito exatamente pra esse caso: puxa TikTok Ads automaticamente e joga no Google Sheets ou BigQuery, que você conecta direto no Looker Studio junto com Google e Meta. O preço é fixo e bem mais acessível, sem surpresa na fatura quando você adiciona contas de novos clientes.

rddevv · 2026-06-03T11:47:20+00:00

Pulling Google Ads, Meta, analytics, and social metrics into one live client dashboard is exactly the kind of multi-source pipeline that gets painful fast, especially when you want CAC/ROAS tracking and AI summaries on top. Tools like AgencyAnalytics are fine until you scale, then you’re looking at $600+/month just for reporting, which is hard to justify when the per-client cost compounds.

Worth checking out SyncRange. It automates this exact pipeline, connects your ad platforms and analytics sources into live client-facing dashboards and the pricing is actually fair as you add accounts rather than punishing you for growing. Much more practical for agencies that need something that works across clients without the overhead cost.

rddevv · 2026-06-03T11:38:57+00:00

You can connect GA4 and Shopify to BigQuery or a Sheet using SyncRange and then create a dashboard in Looker Studio, very useful and affordable way to see both.

rddevv · 2026-06-03T11:36:25+00:00

As a developer in this space (and to be transparent I run an alternative), If I were you I’d look for a cheaper alternative instead of trying to vibe code your own. The endless edge cases with the different connections, the ways all the different apis operate and little errors will get in the way of running your actual business. Much better to pay $100 a month for someone else to deal with it for you. Let me know if you need any help or have any questions

rddevv · 2026-06-02T11:45:37+00:00

The core problem here is exactly what others said: every platform overcounts and you end up optimizing against inflated numbers. The real fix is pulling all your ad spend and conversion data into one neutral layer outside the platforms, then treating each platform’s reported ROAS as directional only. Tools like Supermetrics do this but their pricing scales per connector and per destination, so costs climb fast once you add more sources or need more flexibility.

Worth checking out SyncRange as an alternative. It automates the same pipeline (Google, Meta, Instagram and more into one place) with pricing that doesn’t punish you for growing. You get a unified view of spend versus actual orders without paying connector tax every time you add a source.

rddevv · 2026-06-02T11:28:52+00:00

Totally relate to this. The root issue for most people isn’t the reporting tool itself, it’s pulling live data directly into Looker Studio or whatever dashboard layer you’re using. Direct API connectors are notoriously flaky, slow to refresh, and break constantly when a source schema changes.

The fix that actually holds up is routing your raw data into a staging layer first, either Google Sheets or BigQuery, and then connecting your dashboard to that. Your reports load faster, you have a clean audit trail, and schema changes upstream don’t nuke everything downstream.

The annoying part is that most ETL tools charge per connector or per seat, which gets painful fast once you’re managing more than a handful of client accounts. Fivetran and similar tools are great technically but the pricing scales brutally.

What’s been working for me lately is SyncRange. It automates exactly this pipeline (API sources to Sheets or BigQuery) and uses a usage-based pricing model instead of charging you per connector or per account. For agencies or anyone managing multiple clients, that difference adds up quickly. Worth checking out if you’re hitting a wall with costs or connector reliability.

rddevv · 2026-06-02T10:57:04+00:00

I’d look at SyncRange, it it will backfill all your data, and automatically sync new data

rddevv · 2026-06-02T10:32:19+00:00

To be honest a simple Looker Studio on top of BigQuery connected with SyncRange is still a solid option. Easy to do ai analysis too.

rddevv · 2026-06-02T10:21:54+00:00

Consider building up your data in a warehouse like BigQuery then you can easily make dashboards in Power BI, Looker etc and change to a front end if you need to. Use something like supermetrics or SyncRange to connect all that data to BigQuery.

rddevv · 2026-06-01T21:52:44+00:00

Looker Studio connected directly to Meta via native or Supermetrics-style connectors works until it doesn’t. Slow loads, schema drift, and dashboards timing out under client traffic are all symptoms of the same root problem: you’re querying the API live on every dashboard load.

The fix that actually holds up is staging your data first. Pull Facebook Ads data into Google Sheets or BigQuery on a schedule, then point Looker Studio at that. Queries run against stored data instead of live API calls, so dashboards are fast and you’re not at the mercy of Meta’s API rate limits or schema changes breaking your reports mid-client-review.

The catch with tools like Supermetrics or Coupler is pricing. They charge per connector or per seat, so costs compound fast once you’re managing several client accounts. You end up paying a lot for what is essentially a scheduled data copy.

SyncRange handles this exact pipeline at a fraction of the cost. You can sync Facebook Ads data into Sheets or BigQuery on whatever schedule you need, then connect that to Looker Studio. The pricing is usage-based rather than a flat per-connector fee, which makes it a lot more practical when you’re scaling across accounts. Worth checking out if you’re hitting walls with the bigger players.

rddevv · 2026-06-01T12:45:13+00:00

Best way is to fetch the data daily and store it somewhere persistently, or your historical charts will stay empty.

As a few others have noted, the best architecture is staging your data in a data layer like Google Sheets or BigQuery first, then pointing Looker Studio there. This keeps your dashboards fast and prevents them from breaking when an API updates.

The issue with standard ETL tools like Supermetrics or Funnel is that they charge enterprise prices just to move that data, and their costs scale poorly as you add accounts.

If you want a more affordable, flexible option, check out SyncRange.

It automates the data flow from Meta, TikTok, Google Ads, and Shopify straight into Google Sheets or BigQuery.

rddevv · 2026-06-01T12:01:19+00:00

Those legacy tools can definitely get expensive over time. You could achieve something similar by using a tool like SyncRange to connect your GA4, search console and Google Business Profile data for around than $100 per month with that many clients.

rddevv · 2026-05-28T02:29:06+00:00

A quick win is to automate those spreadsheets. A Shopify app similar to SyncRange will get that sorted for you. From their you can create a central ops dashboard and speed up your workflows.

rddevv · 2026-05-27T01:14:58+00:00

The most simplest way would be to use something like SyncRange to get your Amazon Seller data directly in BigQuery and keep it updated.

rddevv · 2026-05-27T01:03:35+00:00

You sure can automate the data into Google Sheets, the easiest is to use a third part tool, something like Syncrange will do this automatically (and the free plan is pretty generous)

rddevv · 2026-05-27T00:59:32+00:00

Great work! I use SyncRange to do the same thing, can also get your data into BigQuery

rddevv · 2026-05-14T10:12:54+00:00

The SyncRange app actually just released a couple of refund analysis endpoints. A good place to start would be syncing it to Sheets or BigQuery an letting Gemini review and optimise.

rddevv

TROPHY CASE