ShopifyQL Notebooks , 7 条评论

整体评分
2.6
每个评分等级的数量
  • 14% 的评分是 5 星
  • 43% 的评分是 4 星
  • 14% 的评分是 3 星
  • 0% 的评分是 2 星
  • 29% 的评分是 1 星
2024年3月13日

As a long-time user of Shopify's services, our recent upgrade to Shopify Plus came with high expectations. Among the promised benefits was access to an enterprise-grade data visualization tool, ShopifyQL-Notebooks, touted as the solution for all our data querying needs. However, after diving into this tool, I can't help but express profound disappointment.

One would assume that with the substantial investment into Shopify Plus, a sophisticated platform would accompany it. Unfortunately, ShopifyQL-Notebooks falls far short of this mark. It's as if Shopify threw together a rudimentary tool and called it a day, without considering the actual needs of their enterprise-level customers.

One of the most basic queries any e-commerce business might want to run is to find out how many orders need to be shipped out. Shockingly, ShopifyQL-Notebooks doesn't even offer this fundamental capability out of the box. This is basic functionality that one would expect from any modern e-commerce platform, let alone one that positions itself as a leader in the industry.

But it doesn't stop there. Even attempting to delve into more complex queries reveals the stark limitations of this tool. Want to find out how many orders are in a particular status? Forget about it. Need to analyze orders containing specific products? Good luck with that. The dataset provided by ShopifyQL-Notebooks is so abysmally limited that it's practically useless for any meaningful analysis.

It's clear that ShopifyQL-Notebooks is nothing more than a half-baked MVP that Shopify has neglected to invest in further.

In conclusion, if you're considering Shopify Plus in hopes of gaining access to robust data visualization capabilities, don't hold your breath. ShopifyQL-Notebooks is a glaring example of unfulfilled promises and missed opportunities. Save yourself the frustration and look elsewhere for a solution that actually meets your enterprise-level needs.

A . I . S T O N E
美国
4天 人在使用应用
2023年12月18日

would be an absolute game changer, could replace other v expensive reporting apps

but alas, the mere half baked existence of this tool is worse than if they published nothing at all

there are only three (!!) datasets available for query-- product, orders, and payment attempts of all things

what about customer? what about filtering orders by customer type? what about discounts? how is it that i can glean exactly 0 customer insights from this tool?

also the tutorial page is innacurate and the docs website doesn't allow you to leave feedback on the docs

do it right or don't do it at all

MASA Chips
美国
2天 人在使用应用
2023年8月8日

Very cool function, but the app doesn't retreat the latest data from the shop.
For example, even though I wrote to show the data until today, it showed the data up to 2 days agao.

It would be great if the freshness of the data can be improved.

Mister Sandman
德国
6天 人在使用应用
2023年7月30日

great app and one of the first dashboards ppl actually look at... We'd would really love this to work at an organisational level for shopify PLUS. Would also love to group/filter etc by product tags.

Wetsuit Warehouse
澳大利亚
5分钟 人在使用应用
2023年3月9日

This level of reporting (and the fact that I can query ShopifyQL over the API) is exactly what Shopify has been missing. Please shopify: throw buckets of money at improving this feature, it's exactly what every serious store needs to make sense of their sales data.

Rainbow Shops
美国
3个月 人在使用应用
编辑时间:2022年11月15日

We applaud the effort to provide a query language based app to Shopify. Currently, the app fairly limited, with missing columns, and no clarification what is meant (in the app) by 'Orders' and 'Sales' (both sourced as 'Orders' in the app), but are two very, very different files (Sales and Orders) within Shopify itself. We look forward to a more robust update, and larger data dictionary to what's currently offered, but it's a nice start.

The Game Steward
美国
26分钟 人在使用应用
2022年12月6日

pretty cool, I like to usepretty cool, I like to usepretty cool, I like to usepretty cool, I like to use2

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