Saleor is designed with a GraphQL API that gives your developers total front-end freedom to build the storefront that works for your business in whichever technology you prefer. You create a brilliant design but, even though it looks good, how do you know that it is leading customer journeys in the most effective way and driving up conversion rates and average order values?

Changing minor elements of your online store — such as the color of a single button or the size of product images — can have a major effect on a customer’s decision-making process. Seemingly trivial details can be the difference-maker for the success of your business.

A/B testing allows you to offer ever-improving user experiences and get a better return on investment from your online store. Here’s how it works and what it can do to elevate your e-commerce business.

After testing, Yuppiechef increased conversion rates 100% by removing a single distracting element from the page. (1)

How does A/B testing work?

Saleor’s extensible API allows you to create different versions of your store, which you can then measure against one another to work out which design works best and then make informed business decisions.

Let’s take a simple example. You have a grey ‘buy now’ button under the products on your online store; A/B testing would allow you to create multiple variants of your store with orange, green, and blue versions of the same button. You then have four different storefronts; which one a new visitor sees is equally and randomly assigned, meaning each version is seen by 25% of customers. By running this test for a week, you may get a result that looks something like this:

It’s clear that the green or blue color is better for business than the other options. In this case, you might choose to implement a green button as your new standard (baseline) for your storefront. However, it makes sense to run another set of tests with only two versions of the button — green or blue — to validate your results and make sure that green is the best option.

A typical test would run for perhaps a week, or a number of user visits. You can then implement the results into your page design and move onto the next set of tests. It is important to take this incremental approach, as changing a number of elements at one time will make it impossible to clearly identify which factor is influencing results.

Limitless experimentation

A/B testing is an iterative and proven way to test and improve almost any part of your page design, such as:

• Product photos: The type of photography, size and number of images per product, whether zoomable or popup images are better.
• Placement: Every button, element, advert, text box, and image can be tested in different places around to page to see how it affects conversion rates and user experience.
• Copy: Test different slogans and headlines, font types and sizes, lengths of text, and levels of description. For example, Booking.com is almost continuously running A/B tests (2) and tries out alternate texts against one another to find the perfect description for different types of accommodation — because what works for a luxury hotel may not work for a cheap and cheerful B&B

Interpret and take action

A/B testing will often give you results that work against your intuition. But do you argue with clear data-driven results or try to interpret them to understand your users better?

For example, in Saleor, you can build a modern single-page store checkout or you can use the API to create a more traditional 3-step checkout (with separate pages for billing, shipping, and payment).

Your intuition tells you: Your young user base will prefer a modern, single-page checkout.

A/B testing results show you: A traditional three-step checkout leads to 50% less abandoned carts.

Your interpretation of the result: Your young shoppers use mobile devices. A traditional three-step checkout makes for cleaner information on smaller screens while the single-step checkout looks cluttered.

Your next step: Test different setups of a three-step checkout in subsequent experiments to find the perfect version for users.

You can continually run tests of different variants to enhance and evolve your storefront. As you remove pain points, you make it easier for customers to navigate your products, which reduces bounce rates as you have less frustrated shoppers abandoning your store when the UI does not work according to user expectations. You also increase the value of your design work as conversion increases.

A vital tool for modern e-commerce businesses

A/B testing also makes a lot of sense from a business point of view. The cost of running tests with Saleor Cloud is minimal as the platform comes with out-of-the-box A/B testing, unlike most competing platforms which rely upon third-party extensions. The costs incurred are fractional charges connected to the additional consumption of AWS services. However, the savings to business are huge. When one UX decision can either increase or cut conversion rates by half, the risk of making a mistake is nullified when you can scientifically measure the value of every design decision.

There are plenty of elements that make Saleor Cloud the right e-commerce platform for your business. We’ve spent a number of years building a headless commerce solution that offers ultra-fast, dynamic, beautiful anywhere experiences. Saleor’s A/B testing is a validated application, built as a seamless integration to the platform, with a dedicated section of the dashboard for experimentation in your store, as well as an SDK for developers to easily implement A/B testing on your storefront.

By finding the easiest way to bring data-driven tools into your business, you are taking the shortest route to future success.

Read our follow-up article, coming soon, that shows how to avoid some of the pitfalls when running experiments and outlines the best way of getting results you can immediately interpret into informed decisions for your business.

And find out more about the work of our Data Science team in these popular articles about adding Recommendation Systems to your e-commerce.

Contact us at hello@saleor.io to discuss how Saleor Cloud can bring data-driven insight to your e-commerce and super-charge growth.

(1) https://www.designforfounders.com/ab-testing-examples/

(2) https://medium.com/booking-writes/a-b-tests-and-copy-what-why-how-8cc4ae17eae2

Originally posted on Saleor Blog: Super-charging E-commerce with Constant A/B Testing.

Super-charging E-commerce with Iterative A/B Testing was originally published in Saleor on Medium, where people are continuing the conversation by highlighting and responding to this story.

We’re going to talk about explicit and implicit data in Recommendation Systems, especially looking at the problems that negative or unclear responses can cause. It helps to know something about the subject upfront. If you are new to the topic, you can catch up by reading the first two articles in this series that will walk you through it:

• Building Python Recommendation Systems that Work (Jakub Cwynar)
• Everything You Need to Know Before Building a Recommendation System (Tim Clayton)

All caught up? Now, let’s start by looking at the two different types of data.

Explicit data

A customer buys a product, rates a film, or gives a thumbs up or down to a post. The customer is clearly showing how they feel about a product. The data we receive is clean and actionable.

Implicit data

A customer views a product but does not make a purchase. A user watches a film trailer or reads an article about something. We’ve got a statement of intent but no clear, affirmative action.

Is one type of data better than the other?

You might assume that explicit data is always more valuable to businesses. It is clear, unambiguous, and gives us a definite picture of the user. However, some businesses may actually prefer, or take more value from implicit data — often because explicit data is much harder to collect. Let’s look at Spotify. Simply listening to a song is not explicit data in itself. The system does not know for sure that the user likes that song. Actual explicit data is when the user adds a specific tune to a playlist or hits the heart icon to say that they enjoy listening to it. But how many of us actually do that? I have personally listened to thousands of songs on Spotify without really noticing the heart button. If you are in the office listening to a recommended playlist in a browser while busily working in a different tab, are you really going to click back and forth to like each song that comes up?

The same applies to YouTube, IMDB, and a host of other websites where people browse and view but do not always leave a rating. In such cases, there is exponentially more implicit than explicit data being created by user activity.

Explicit data can also be shallow. Users may be asked to give binary reactions: like or dislike, thumbs up or thumbs down. Even when a site like IMDB allows for ratings from 1 to 10, human nature means that people tend to rate in the extremes. Users regularly rate everything as 10 or 1; not many people take the time to leave a 4-out-of-10 rating because they clearly didn’t have a strong opinion in the first place.

The leading builders of Recommendation System have learned to harness the abundance of implicit data, understanding as much from suggestion as they do from clear and explicit reactions.

Are explicit and implicit data weighted differently?

Explicit data will always have more obvious value than implicit data, and will naturally be favorable (if, as highlighted above, users can actually be encouraged to give enough clear feedback). The main reason that implicit data is harder for companies to interpret is that it requires clarification. Explicit data is one-action feedback: a single click tells us that a user liked a video or rated a product positively. With implicit data, we sometimes need to observe what the user does next. If someone listens to a single song, we cannot know if they liked that artist. The system needs to store that information and see what happens in future. If the user then purchases an album download a few days later, that second action backs up the initial assumption. The system can then learn how that single user or all users interact with the system and make better assumptions as time passes and more data is generated.

How do the best systems learn from user behavior?

Each person is unique. Although sites are designed to encourage us to interact with them in certain, predictable ways — to create the clearest user paths — we all still behave differently.

My wife and I love watching movies together, but we certainly don’t enjoy trailers in the same way. To decide if she is interested in a film, my wife will watch the entire trailer — sometimes more than once. If she is not interested in a film, she will turn the trailer off within ten seconds.

My behavior is the polar opposite. I can usually tell if a film is going to interest me within the first ten seconds of the trailer. I will then switch it off immediately to avoid any spoilers. If I am not interested in a film, I will watch the entire trailer (although now that I actually see that in writing, I have no reasonable explanation of why I do it).

A really good Recommendation System also has to learn to interpret and explain opposing behaviors. If my wife and I both stop watching a trailer on streaming service after ten seconds, it may be right to assume that neither of us is interested in the movie. If I then go back and watch the film within the month and my wife does not, that tells the system a little something about our behavior. If we then repeat that behavior several more times, the most powerful Recommendation System will be able to interpret my seemingly negative response as a positive signal. However, as with almost all implicit data, it requires confirmation of the initial assumption.

How do systems deal with negative ratings?

Whether explicit or implicit data, the biggest challenge for Recommendations Systems is often in dealing with negative feedback. If, for example, a user watches ten heavy metal videos on YouTube and gives them all a solid thumbs down, what does the system learn from our activity? Does it stop showing the user Metallica in the recommendations list because he repeatedly had negative reactions to metal music? Or does it decide that he watched ten metal videos in a row and, therefore, suggest more of the same (because, presumably, the user is a glutton for punishment)?

In reality, it depends on the goal of the system. If the aim is to simply keep the user consuming content, because the revenue comes from advertising income, the Recommendation System will probably suggest whatever content the user is willing to consume. If the aim is to drive sales, the system will be more inclined to try and show the user products or content that he or she will actually like. When you have an online store in which users can rate items of clothing, you don’t want your Recommendation System to keep showing red dresses to a user who negatively rated everything in that color, as it is unlikely to lead to a sale. You don’t want your user to see red.

What if a user doesn’t interact at all?

If you have an online store with two rows of products and you find that people are only clicking on the items you present to them on the first row, what does it really mean? When your recommendation engine decides upon the products that users see, is it so perfectly calibrated that users’ favorite choices are always the first row? Or is there something lurking beneath?

Users could be only clicking on the products in the first row because they are of most interest, but it could be a problem with the UX. Maybe the site is designed in such a way that the second row is not displayed prominently and doesn’t catch the eye. Remember, I love Spotify, but didn’t notice that little heart that lets me confirm that I like a track… which perhaps means that maybe it is not working in the way it should.

It is therefore not enough to implement a Recommendation System and take the results at face value. You need to ‘A/B test’ your results as much as possible. Test the system against a second version of your store without the system running, so you can measure results. Then test different versions of your interface against one another to see which works best for business.

This is a key element of our own upcoming Saleor Cloud e-commerce solution. You can build multiple versions of your storefront to check that you are getting it right.

You don’t have to go so deep

Some of the explicit and implicit data issues in this article are only important for some of the world’s biggest companies. However, it does give you an overview of the deeper data analysis that is going on even for less complex systems. In the first articles of this series, we discussed how you can make a recommendation system of your own and we then answered some of the FAQs you might ask before you get started. If you are going it alone, we wish you successful and profitable recommendations! If you are looking to build something more complex or want us to do the hard work for you, feel free to contact our data science department and let’s start the conversation. They come highly recommended!

Still hungry for more about data? Check out how far Netflix takes its recommendation system. It’s a great read and helps put the content of our three-part series into a fresh context.

Artwork Personalization at Netflix

We love to hear your thoughts on our thoughts, so please leave a comment.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

In the first article of this series about Recommendation Systems, we discussed how they work and gave some simple tools that anyone can use to get started. The best place to start is to check out that article, but if you need a quick refresher, here are the basics:

• Recommendation Systems collect data on user behavior and predict which products or services will be of interest to them
• When users have similar histories and preferences, the system presents User B with recommendations that User A liked
• The basic job of a system is to fill in the gaps, deciding if a product that a user has not seen or interacted with will be of interest to them

If you want the simplest possible example, click ‘Your Discover Weekly’ on Spotify and you will be given a list of songs that you have never played on the platform but which the recommendation system believes you will like based on your listening history.

In the next two articles, we are going to go deeper, starting with some of the most common questions that come up when businesses think about building a Recommendation System.

Are Recommendation Systems good for any business?

The first question you need to ask when creating a Recommendation System (RS) is whether your users are generating enough data to make it worthwhile. It costs time and money to implement a good system. If your solution is not going to be effective for business, your valuable resources would be better spent elsewhere.

In Spotify, YouTube, Facebook, Netflix or Amazon, regular users are looking for ever-improving personalized experiences. As they use the system more, the recommendations should become more specific and more accurate.

If people only visit your store once or twice, you can’t offer that experience; but that doesn’t mean an RS is useless. Rather than having a personalized system, you can collate the behavior of all your users to make more general recommendations. For example, if a new user clicks on a specific coat in your store, you can recommend a scarf that was also purchased by previous customers who bought the coat.

In this scenario, almost all businesses can benefit from Recommendation Systems; the only time that it is unlikely to have any business value is if you have a limited product range and very low site traffic. If you offer only a few high-value products, which you sell infrequently, then the effort behind an RS may not be worth it.

How many data points do we need to start?

How long is a piece of string? Many people accept the minimum threshold of 1,000 respondents before survey results can be published. With Recommendation Systems — as with opinion polls — the rule of thumb is “the more data the better”.

If we only sold 8 packs of diapers in our online store, but everyone who bought diapers also purchased diaper disposal bags, we have a very limited data set but a 100% correlation. It’s fair to say that our store should recommend disposal bags to every new user who views diapers. Of course, the trend may change as we gather more data over time, but the initial assumption is solid. We don’t need 1,000 people buying both products before we call it an upselling opportunity.

A good Recommendation System is one that can spot trends as soon as they emerge and use future responses to confirm or disprove the assumption. And more data does not always mean clearer insight. And if a million people like Game of Thrones on our ratings site and 50% of those people also like True Detective, we can’t draw any strong conclusion.

Pretty Green case study: How to scale global e-commerce business | Mirumee

When is one user a good fit for another?

Everyone is unique. My former best friend and I agreed totally on music and films. We were 100% matched until he told me that he doesn’t like Pearl Jam… We never spoke again.

An RS will never be able to match User A to User B with perfect results, as their tastes will diverge at some point. If two users both rate 9 bands as good but differ in their opinion of the tenth, they are still a very strong match. If User A rates the eleventh band as good, we should still assume User B will like them. But at what point do users stop being a good match? 90% compatibility? 80… 60… 40?

The truth is, recommendation engines don’t set a threshold when looking for compatibility between people; they look for the best possible match. If we have a user, Alice, who has a 95% compatibility with Bob, 80% with Carol, and 30% with Dave, the system will start by looking at Bob when deciding if Alice will like a certain band. If Bob has not given a response to that band’s music, the system will move on to Carol, and then to Dave. The more users we have in the data set, the more likely it is that a person with a high compatibility will give a response that the system can leverage.

Are user matches or product matches better?

We are discussing two basic types of recommendation here. The first is user-to-user, in which we see that User A is similar to User B and make suggestions to User B based on what their ‘digital twin’ bought or browsed. The second is product bundling, in which our scarf and coat were popular choices together, as were the diapers and the disposal bags.

The best Recommendation Systems are able to utilize both sets of parameters to extrapolate the very most from the data. But there are rules of thumb that are worth considering. For example, in an online store, while your customers are browsing products, you might want to focus on user-to-user recommendations and show them products that similar customers liked. Once they are in the checkout and have the items in their cart, you might want to push product bundles. For example, if someone just has the diapers in their cart, a good system would remind them to add disposal bags before they pay the bill.

When should I implement a cold start engine?

Cold starts, as described in the previous article, are when a new user comes to a site and we know nothing about them. So, how can we start making recommendations to give them the best possible experience from their first visit?

Sites like Netflix ask new users to select a few movies they are interested in before entering the site for the first time. If the new user chooses ten romcoms, Netflix will probably suggest Maid In Manhattan and The Big Sick.

Whether you need a cold start engine depends on your product range. If you are a men’s hiking apparel store, you have a niche of products and your users are likely to be men who like day trips in the mountains. You don’t need to refine the content the user sees.

However, if your clothing store sells to women and men of all ages, across a range of fashions and functionalities, you might want to work out who is viewing your page so you can present them with items they might buy. In this case, your cold start engine might be a dozen pictures of men and women in different clothing. By asking your new user to click on the picture that matches their style, you can find out in one click that your new, unique site visitor is a teenage girl who likes a sporty style.

Of course, you can quickly find out the same information as the user starts browsing, but one click might be the difference between a satisfied customer and a bored browser, so it is worth it if you have a wide customer demographic and a large product range.

How do I know if it is working?

The bottom line is always the bottom line. If your Recommendation System is working, you will see a growth in sales. However, if we assume that a 1% growth in sales is a significant change, how do we know that the success is down to our Recommendation System and not our marketing, or product trends, or the failures of our competitors? If we are investing in something, we need to know that it works and is worth pouring more resources into.

The answer, A/B testing, is also a key, standard feature of our upcoming Saleor Cloud solution. By creating 2 different versions of our store — one which utilizes our Recommendation System and one which does not — different customers see different versions of the storefront and we are able to observe which is more effective, both in general and for sales of specific products.

Essentially, we use hard data to check if our data-driven recommendations are working. Is there really any other way?!

If you are thinking about building a Recommendation System for your e-commerce, feel free to get in touch and speak to us about your project.

Read the next part of this blog series:
The Difference Between Implicit and Explicit Data for Business

We love to hear your thoughts on our thoughts, so please leave a comment.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

We never really consider our design work to be completely done. Web design, particularly in open source projects, is always subject to future changes and iterations. However, the release of our Saleor 2.0 platform in November 2018 was a major landmark and is a great opportunity to take a look at the visual journey of the Saleor brand so far. It’s also a chance for us to recognize the great work of our design team… who have asked me to remind you that “It’s all still a work in progress (and always will be).”

Let’s start at the beginning…

2010–2017
Setting Sail

Saleor was the fastest growing open source e-commerce solution in the world in 2018, but it has taken time to get to that level. Way back in 2010, we built Satchless, a pure-Python library providing generic e-commerce interfaces. It was a building block used to provide features like checkouts and carts. Taking this as our cue, the Satchless branding motif we designed was — you guessed it — a fancy retro shopping cart, along with a traditional striped shop awning in the logo.

In 2012, we split off the Django-specific part of Satchless under a new brand, which we named Saleor [pronounced ˈseɪlə(r)] because we felt like it was something that floated along under the radar, and the name just flowed. We designed a mashup of viking longboat with a merchant ship, reworked the Django symbol as the figurehead, and kept some continuity with the Satchless design by changing our striped awning into the sail.

2017–2018
Into the E-commerce Ocean

Saleor gained so much traction that we knew it was time to push the solution and build our first complete branded website, for release in early 2017. As an e-commerce platform created by developers for developers, we focused on communicating with that target group in our first designs. We stuck with the familiar ocean theme but switched from vikings to pirates, because developers often identify with freebooters charging around in international waters. The style was cartoonish fun as most of the developers we know love animation — from the Cartoon Network to the utterly obscure.

The pirate (who has no official name, but I like to think of him as Salty) became a recognizable avatar among developers, but Saleor grew so quickly in 2017 that we soon realized we would have to take it beyond the dev community and out into the wider business world. The style we had created wasn’t one that would have a strong appeal for business decision-makers.

Here is the interesting question: Did we get it wrong first time around? Was it all too cartoonish and light-hearted? After all, we started a major redesign only a year after the first version was launched. In reality, it is the perfect illustration (pun intended) of how design is always iterative. The code we were writing was good and we found, over time, that there was a market need that we could fulfill, for which we needed to take a wider perspective. Our initial design more than answered the brief. It attracted a community that helped us attain a level of success. The knock-on effect was that we had to move the branding on as our horizons changed.

Check out the full Behance overview of the first full design package for Saleor here: Saleor 1.0 brand overview

2018
A Path to the Stars

In early 2018, we made a fundamental technology decision to enhance Saleor with a GraphQL API. It signaled the major change that required us to re-brand Saleor. We wanted to reflect the modernity we were now bringing to e-commerce and refocus our developer-first image into a darker, more cyber-inspired tone, drawing on the fresh visual language of leading cryptocurrency websites.

We created the visual branding at the same time as we were building new page templates and architecture. This meant that everything was designed with a consideration for how it would look on the final page, and every small element of our brand identity had to be reconsidered. At times it felt like we were taking one step forward and two back, but the design began to take shape.

The Saleor 2.0 Design Process

We started by updating our brand profile to bridge the gap between our existing community of developers and business decision makers.

We made early decisions about aspects of the visual branding:

• We wanted a theme that would reflect the established brand name and also retain some consistency for our developer community.
• We liked the idea of using versatile geometric shapes, as knew we would have a huge number of assets to produce in the future and would need flexible design elements. We also felt that the isometric style was a great fit for Mirumee Labs and Saleor.

Early ideas for our key visual included a stylized anchor, a humble shipping container, and an iceberg (with the tip representing the work done by store owners and the underwater section being the stable base of Saleor). They all had merit but we wanted a find a link to the original branding that wasn’t tied too closely to shipping.

Searching for something that felt new but was a nod to the past, we hit upon the idea of creating a modern, ‘cyber’ version of the parrot, which was a supporting character in the original branding images. We drew a bird with digital strands inspired by the inside of a microchip and by computer connectors. It was thus rooted firmly in the world of IT and was a strong, technical, even mathematical piece of design.

This really created the visual story we needed to tell. Saleor 2.0 was an evolution of the existing platform and our branding was able to reimagine one specific element of the original design and take it into the new identity in an exciting way.

The New Saleor Logo

We wanted a logotype that was simple and elegant, and yet bold. We chose Heron Sans for the font, because it looked modern and technical. While working on a brand signature in the shape of a 3D shopping bag, with the letter S on the front, we came up with the idea of erasing the outline of the lower section to leave a suggestive, bold signature.

It was another lightbulb moment. The remaining element was also similar to the shipping container that had been at the start point of our design process — but one with the ends shaped like forward slashes used in coding:

// The mapping between latitude, longitude, and pixels is defined by the web // mercator projection.

It’s subtle but still bold and simple enough to be versatile. It is also open to small changes whenever we create related products or extensions of the Saleor brand.

The whole rebranding process was a time and resources challenge but a great opportunity to create a fresh and dynamic identity for a brand that we love. We also had a chance to learn new techniques for creating dynamic animations for the net, which the Lottie plugin allowed us to export directly.

You can view the rebranding of Saleor 2.0 on Behance. Follow our page to see more of our design work.

Originally posted on Saleor Blog: The Iterative Rebranding of Saleor.

We love to hear your thoughts on our thoughts, so please leave a comment.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation, to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

The Iterative Rebranding of Saleor was originally published in Saleor on Medium, where people are continuing the conversation by highlighting and responding to this story.

DjangoCon Europe is run by the community for the community: which is what makes it just the kind of event we absolutely love to attend. The 11th edition took place in Copenhagen, from 10 to 14 April, and we sent 4 Mirumeers along to get involved in the discussion and workshops that aim to educate and develop the skills of the growing Django community. It was a fun event that gave us a fresh perspective on the current state of Django… and the ramen was pretty good too!

Untamed Creativity

A good conference starts with a great space, and DjangoCon delivered in an inspiring and unusual way. The Academy for Untamed Creativity is a place normally dedicated to the training of circus arts to people who want to get into the entertainment industry. It offered the kind of playful, creative environment that was ideal for a group of developers looking to push technological instead of physical boundaries.

Standing room only

We were able to make our own contribution to the event in a workshop, run by Marcin Gębala, Project Lead of Saleor, and Patryk Zawadzki, our Head of Tech, presenting the basics of building GraphQL servers in Python using Ariadne.

We started with the most important concepts then worked through creating an example query with a resolver and a mutation. We also wanted to give a sneak peek into Python of the future — asynchronous subscriptions with Ariadne, Django Channels 2.0, Starlette, and asynchronous database access!

With 40 people attending, it was standing room only by the time we kicked things off. It showed a lot of excitement for what we are doing and convinced us that we are at the forefront of async Python, helping to shape the future of web development in Python. Many developers still don’t see the full value of the async model, or of changing from familiar tools to accommodate a new way of doing things, but we are strong advocates for taking that step and were excited by the response we received.

We’ll be sharing more about the talk and a full tutorial in a future post, so keep a look out over the coming weeks. For now, you can see the slide from the talk here:

Creating a GraphQL API in Python: from Django to fully asynchronous

Docs or it didn’t happen

If you have ever seen Mikey Ariel in action, it will come as no surprise that her “Docs or it didn’t happen!” talk was one of the absolute highlights of the conference. Developers often overlook documentation but writethedocs.org does such an awesome job of providing writing aids and workshops to advocate for better practices. The talk offered up a lot of nice tools and resources and was a great example of passionate people spending their time and effort to make technology better for the whole community.

It’s something that also speaks clearly to us in our current projects. We’ve kicked off work on Saleor Cloud, a hosted version of our e-commerce platform, and we had already decided that a docs-first approach was the way to build the right technology.

Follow Mikey on Twitter and get in touch with your docs side.

The future of Django

One of our main takeaways from the conference was that async is the future of web frameworks; it is generally on the rise in the Python community but is not widely adopted in the Django community yet. It is a similar story with GraphQL, but the amount of talk we heard from people over the course of the three days told us that change is coming.

It was great that Tom Christie, an author of the Django Rest Framework, and a leading figure in the Django community, sees things the same way that we do. He talked about a move towards asynchronous architecture and presented some experimental tools that he’s working on such as an async web framework and async database drivers. We were also stoked that he also mentioned our own Ariadne project as an emerging Python tool.

We were also excited to have a chance to chat to with Tom after this presentation and dive deep into ASGI. We’re definitely going to continue supporting ASGI and the Starlette stack and are looking forward to what the future brings there.

Next on the agenda, Marcin Gębala will be speaking at PyCon Italia in Florence and PyConWeb 2019 in Munich, before we head to the GraphQL conference in Berlin in June. we are sincerely hoping for more circus acrobatics and some really great ramen.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

Patch helps you find the best plants for your space, delivers to your door and helps you look after them.

It’s an overused word nowadays but Patch are true disruptors. By specializing in online sales of plants to young city dwellers, encouraging them to create “urban jungles”, they have brought a new model to a traditional business area and managed to acquire 25,000 customers within 2 years of launching their Saleor-powered website. Tyler Hildebrandt, Head of Engineering, talked to us about his own journey to Patch as well as some of the innovations and good business practices that have propelled the company into the top 30 of the UK’s #Startups100 ranking.

Patch and Tyler

“I came from Canada to the UK a decade ago and worked on projects in social media and healthcare before moving into e-commerce. One day, Patch posted a leaflet through the door inviting me to complete an inventory of my living space and my preferences, from which they would create my indoor urban jungle. That was the service they were offering before the e-commerce really took off. It seemed like a fun idea but I put the leaflet in a stack of papers and didn’t think about it again until 8 months later when I received an email asking if I would be interested in a Tech Lead position with them. Then it just clicked into place.

“It probably helps that I am the archetype of an ideal Patch customer. I live in the city and don’t have a garden. I also don’t own a car that I could take to the garden center, just like 46% of Londoners. I grew up enjoying plants because my mother was a keen gardener but couldn’t tell you their names.

“The fact that I was interested in the service Patch were offering made it easy to see the long-term value in joining the company. They had already chosen Saleor as the e-commerce platform when I arrived; it wasn’t my decision but it is one that I am very glad they took.”

Patch and Urban Gardeners

“We like to think of ourselves as the world’s first fun and desirable horticulture brand.

Plants are beautiful and inspiring but urbanites who are brave enough to bring them home often don’t have good knowledge of how to care for them. Beyond just providing a selection of plants, we also aspire to help customers care for those plants so that they can really enjoy them (i.e. not kill them!)”

Patch is a great example of how to engage and excite people about a product:

1. Build a community
Engage 70K plant fans on Instagram with a regular stream of great photos.

2. Share valuable content
Patch provide dozens of free plant-care tutorials and resources to the community.

3. Make it fun
Meet Big Ken the Kentia palm, Penny the money plant, and Charlie the elephant plant (so named because the floppy leaves resemble the ears of Tyler’s own dog).

4. Continue the journey together
Growing with clients is essential. Patch are working on an offering to help new plant lovers to build full allotments or gardens in the city.

Patch and the Horticulture Industry

“Our sector is a strange mix of the high-tech and the traditional. We visited growers in Holland last year and were blown away by the level of technology and sophistication that they’ve added to their centuries of experience. On the other hand, the plant industry is largely traditional: growers produce the plants and send them to garden centers, customers then purchase them on sight and load them into their cars.

“E-commerce itself is not always disruptive but the plant business faces unique challenges. Plants can be both unwieldy and delicate; they are sold like a commodity but are perishable like a foodstuff; they need to be stored but don’t retain their value if they are kept in a warehouse. Also, we present clients with a beautiful picture of a specific plant on our website or Instagram, but the product they get will be different, as each plant is unique.

“We’ve have had to overcome so many things. Traditionalists in the industry were skeptical at first, but I think they were also excited by our vision and wanted us to succeed.”

Patch and Saleor

“We have a four-person development team. Our storefront is based on Saleor and services are run in containers in AWS. We’ve built in numerous integrations to support our operations and logistics, working a lot with AWS Lambda using both Python and Go. Being able to do what we want with great flexibility and never have Saleor ‘get in the way’ is paramount — and sometimes Saleor jumps ahead of us by solving issues before we get there. We frequently check in to see how we can blend it all together to overcome our challenges.

“The community behind Saleor is a huge advantage; they are constantly improving the solution and delivering great updates. It has evolved from a simple Django setup into a nicely constructed, modern, GraphQL API-driven piece of technology.

“In a market like London, good developers earn a decent wage and they have the pick of where they work. They need engaging tasks using productive tools or they move on quickly. Saleor is a fun platform for developers that they can work with easily and efficiently. For a startup, that is a huge factor in being able to retain talent and sustain growth.”

We want to thank Tyler for the interview and the chance to talk about the remarkable success of Patch and Saleor. After adopting the platform in early 2017, Patch entered a period of sustained growth that saw sales increase consistently at 30% per month. Patch was then able to raise a seed round in August 2017 before successfully closing a series A funding in May 2018.

Find out more about Patch by visiting their website

You can also check out their incredible shots on Instagram

Patch (@patchplants) * Instagram photos and videos

Follow Saleor on Twitter and join the community on Spectrum.

If you use Saleor for your site, contact us through our short survey and tell us how you feel about the platform. You could even be our next featured story if you want to share your success.

Originally posted on Saleor Blog: Saleor In Action: An Interview with Patch.

Saleor In Action: An Interview with Patch was originally published in Saleor on Medium, where people are continuing the conversation by highlighting and responding to this story.

• It’s the last chance to get the most benefit from mobile and PWA
• Time to stop thinking of the high street and e-commerce as separate entities
• Emerging technologies are set to further enhance customer experiences

2018 is in the bag. What a year! Almost everything from May onwards was driven towards the big release of Saleor 2.0. Now that is done, and Saleor is the officially the fastest-growing open source e-commerce platform in the world over the last 6 months, you’d think we would take some down time. But a new year means new opportunities and we are are fully focused on how we can roll with the big underlying e-commerce trends, as well as looking at emerging technologies which can enhance our business. Here is our take on what will shape e-commerce in 2019.

Mobiles and PWA

Mobile shopping took another great leap in 2018. Black Friday broke records in the USA to become the first ever $7 B day for e-commerce, of which $2 B was through mobile. It is not just a US trend, 90% of people in China used mobile for payments on Singles’ Day last year, while emerging markets like Africa are investing heavily in mobile as the most affordable and convenient way of doing business.

Essentially, if you are in e-commerce, mobile has grown to the point where it is now the last opportunity to really get on board. We will be helping companies with that shift.

PWA storefronts will also boom in the coming year. Retailers can offer stores to clients as native-like applications which can be browsed at any time, on- or off-line, giving shoppers a whole new level of retail experience and convenience. This was a key feature of the release of our Saleor 2.0 open source e-commerce solution.

People no longer want to wait for services; they expect everything to be tailored to an on-demand experience. As a retailer, you should use PWA to move away from simply offering products to customers and move closer to offering them experiences.

Mobile-native payments like Payment Request, Apple Pay and Google Pay, which increase convenience with stored checkout details, are another element of the frictionless end-user experience. Every barrier that is broken down, every click saved, and every form that doesn’t need filling in is a bonus, which is why we have solid plans to support these technologies in Saleor in 2019.

E-commerce can help the high street survive

Predictions suggest that over half of the 1,200 shopping malls in the US expect to close by 2023. The UK also had a rocky 2018 on the high street with household favourites like Toys R Us, HMV, House of Fraser and Maplins announcing big cuts or total closure.

The internet has democratized shopping. Consumers are no longer tied to big stores when smaller, independent outlets can offer the same products with more personalized service and online stores can offer cheaper prices. The opportunity for companies like Mirumee in the coming years is to help large retailers who are attempting to transform their business in response to this challenge.

E-commerce will not be a separate business arm of retailers in the future; the stores that thrive will be those with an omni-channel, fluid online and offline experience in which shopping trips may also be augmented by e-commerce technology.

Rather than e-commerce being a challenge to the high street, successful companies who exist in both spaces will see how each can complement and elevate the other.

We have to assess the online and offline activities of our clients; it’s no good just building software, we need to think about the whole brand experience and even offer advice on high street activities if our insight can add value. There really is no division between the high street and e-commerce of the future, it is all just good commerce.

Machine Learning and AI

Machine Learning and AI have been the big topics of 2018; skepticism has died down and people have come to accept the future of computing.

For Black Friday, we implemented our own ML engine for an online retail client who uses our Saleor e-commerce platform. The machine was an enhancement of an existing popularity-based recommendations engine; we added machine learning which analyzed each individual user’s purchase history against items which were frequently bought together, in order to make more targeted recommendations. This more personalized shopping experience achieved an $80,000 revenue increase over the course of 15 days (a spike of nearly 7%) and lifted the conversion rate by more than 1%. The fully automated process allowed the company to increase sales and profits — as well as moving near-obsolete stock — without any additional time spent by staff.

The key to good implementations of AI and ML still lies in human awareness and action. Make sure you know what to do 2 months, 2 weeks and 2 days before an event like Black Friday. 2019 is going to see a lot of businesses trying and failing with AI, because they failed to understand the real power of the technology and use it to its full potential.

Our own ML and AI activity in 2019 will be focused around helping businesses do it right. AI will soon be the norm, so now is the time to get ahead of the market with good implementations.

Social commerce

Social media has been a game-changer for brands and retailers over recent years. Small businesses can reach potential customers without investing heavily in marketing and larger brands can take more ownership of their voice in the public realm. The main challenges are how to maintain a consistent, controlled brand voice and how to generate revenue from customer engagement on social channels.

E-commerce solutions are now starting to merge with major social media platforms, allowing customers to buy directly from their Facebook wall or an Instagram post, removing the additional clicks between interest and conversion. Perhaps surprisingly, Pinterest is the fastest growing social media platform and the one most suited to social commerce. In fact, 88% of people who save pins are doing so in search of a purchase.

Social commerce has existed for some time now, but it is beginning to truly move over to converting leads in real time, and is offering measurable analytics.

Voice commerce

Smart speakers are set to seriously disrupt e-commerce. We love the Google Home device in our office which we use to facilitate our scrum meetings, but we are certainly among the early adopters of an emerging technology that has far more capability than we can currently utilize. We can’t yet use our device to order in lunch in Poland, as they do in America, but change is coming.

36% of US owners of smart speakers have already used them more than once to make a purchase and the figure is almost at 20% in the UK. While the technology is still not catching on as fast in other markets, it still represents a huge market opportunity: spending through voice commerce in the US in 2017 was $2 B, by 2022 it is predicted to be a staggering $40 B. 90% of those purchases are through Amazon but other channels are going to take advantage of the technology soon.

Interestingly, purchases made via voice commerce are usually of products that the customer already knows; it is currently not a browsing platform, only a way to quickly purchase specific, familiar products.

Similar to social commerce and mobile purchases, voice commerce shows that 2019 is not just about the products people buy; we are on the cusp of a revolution in the way that people make purchases. Everything is moving towards multi-channel, multi-device experiences with less clicks, or no clicks at all, removing the obstacles between a lead and a sale.

Both social commerce and voice commerce are areas we want to explore with Saleor. We’re not just playing with our smart speaker because it is a cool toy; we want to understand the technology as an end user, and then think about how we can integrate that into our platforms in the future.

The biggest trend of 2019 is, of course, the same trend that has been ongoing for a number of years; namely, offering omni-channel experiences with a consistent brand identity and value across a number of platforms. The best e-commerce today offers the same great experience and service on any site and on any device, and gives users the chance to purchase products and interact with retailers.

The final thing companies need to bear in mind is that there are so many incredible customer experiences already in the e-commerce space. If your store is not offering great customer service, easy contact with sales and support staff, rapid delivery, and no-questions-asked returns, you are probably already falling behind your competitors.

Whatever you have in mind for 2019, we wish you success. If you happen to be thinking about building an e-commerce solution that will elevate your business and send sales through the roof, speak to us about Saleor, our free-to-use open source solution that is a favorite of businesses the world over, or speak to us about bespoke solutions and services.

We love to hear your thoughts on our thoughts, so please leave a comment.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

• Over 2,000 attendees chose from dozens of talks from speakers representing global giants like Google, Facebook, Audi, and Adidas
• Diversity is still a major issue for tech companies but it is also a major value-add if it can be achieved
• Women don’t have to make the compromises that are accepted as a norm if they speak up with confidence

Nearly 2,000 attendees (most of them female) dropped into Amsterdam for the 2018 edition of the European Women in Tech conference, which describes itself as ‘a celebration of diversity in the world’s fasted growing industry’. The conference itself has grown in just a couple of years to become a massive event, with talks from up to 9 speakers to choose from at any given time. While our representatives, Mira, Weronika and Anna, didn’t manage to see and do it all, there was plenty to talk about.

If you took one thing away from the event, what would it be?

Anna: Diversity was the keyword of the conference but it’s not just about convincing women to get into tech, it’s about how to be successful and fulfill ambitions in an industry dominated by men.

Mira: Dr Carina Kögler, Head of Plant Service at Audi, shared how she had to go with male colleagues to a strip club to try and fit in to the male-dominated world she found herself in at the beginning of her career. Obviously, that was not good for her or the company she worked for at the time.

Weronika: The most powerful remark that came out of the conference was from Luciana Broggi, EMEA GM of Hewlett Packard Inc. It’s great to be talking about diversity but she dreams of a time when we won’t be discussing about it anymore because it will be the norm. That struck a chord with everyone at the conference.

Why does diversity matter so much?

Weronika: There were a lot of talks about why diversity is important for your team and company. It helps build better products because team members can draw upon their own unique cultural backgrounds or gender to find different solutions to problems. In diverse teams it’s also easier for people to share their ideas without fear of being judged.

Mira: Diversity doesn’t work if you only have one or two people who are outside of the norm, as they are then marginalized and excluded. It needs to be more of a genuine balance to really work.

Anna: Diversity is still a huge problem. The presenters from Xing explained how women have worse working conditions. There is still a huge gender pay gap. In Germany, for example, women earn 18.3% less than men in the same positions and there are 17.2% less women in tech positions. Statistics also show that only 31.5% of women with children under 3 years old are in active employment, while the figure for men is 80.6%. Societal expectations make it much more difficult for women to get out to work.

What good advice did you take from the conference?

Mira: If you want to be heard, you have to speak up. Don’t just wait to be discovered; if women sit quietly, our careers will go nowhere and we will only have ourselves to blame.

Anna: Yes, speaking up was a big topic. It was really interesting to hear Alena Hielema talk about how women need to take more ownership of their achievements. Instead of saying “we did this”, which women have a tendency to do, we need to brave enough to say “I did this.”

Weronika: We also heard from some speakers about how to be smart and get better salaries and improved working conditions. Women need to learn how to lead that conversation and ask those difficult questions in a way that gets results.

And the most inspiring stories?

Weronika: In general it was really positive to be around so many successful women in our field who are working in big companies like Google, Shopify, Facebook, Amazon AWS, Zalando, and Adidas. One talk that really stood out for me was Amanda McAlister from ASOS sharing tips on how to integrate team members with one another. They have fun in-house sessions in which people can share about their outside interests. The better relationships they build through such activities help to make work more effective.

Anna: Irana Wasti, Senior Vice President and Head of EMEA in GoDaddy, showed up that combining family life with work is possible and that women don’t have to make the compromises that society suggests we should. It is not a straight choice between career and family. Irana gave birth half-way through an MBA and still has a successful career. She explained how women shouldn’t feel like we have to ask permission to get support from their bosses. We must speak clearly about our needs and not compare ourselves with others. If we push through fear of rejection, we can get what we need to be successful. Daria Dubinina, CEO of Crassula, a company that works in the same e-commerce space as Mirumee, was so sure about what she needed that she relocated from Ukraine to Silicon Valley because she wanted her ideas to be taken seriously. She decided to build her business in a place where a female CEO was treated with more respect.

Any final thoughts?

Anna: Not all of the topics were about women and diversity. I really loved hearing about JOMO from Rose La Prairie, a product manager from Android Digital Wellbeing. We all know about FOMO, the ‘fear of missing out’, and how attached we are to mobile devices. She presented a different way of thinking and showed how even some tech giants realize that we need to be less connected to our devices and get out and live a little more. We shouldn’t be checking our phones as the last thing we do before sleep and the first thing we do in the morning.

Weronika: Indeed, and it wasn’t all soft skills, there were also some big companies talking about technologies we use in Mirumee like Python, React, and GraphQL. It was nice to know that we are in such good company with the things we do on a daily basis.

Mira: Plenty of those successful women with inspiring stories were also very amiable and open to chatting with us in the networking area. Most of all, I’d like to travel back in time to attend all the talks!

Luckily, no time travel is actually needed. If you are interested in hearing some of the talks from European Women in Technology, keep an eye on their website, Facebook and Twitter pages over the coming weeks as they have promised to add plenty of thought-inspiring content.

You can also read more about our own hopes and aspirations to improve diversity in our recent post about the struggle to employ more female coders.

We love to hear your thoughts on our thoughts, so please leave a comment.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

What’s the main takeaway?

• Women are still under-represented in STEM subject studies and in technical positions in the workplace
• Employers who want to achieve gender equality and have more diverse workplaces struggle with a lack of applicants
• Grass roots initiatives to get females into technology offer the hope for the future

We have a problem.

Rather than pretend it isn’t there, we want to talk about it.

We are the number one open source Python contributor in Poland, ranked in the top 500 globally, and the creators of the one of the fastest growing open source e-commerce platforms in the world. We pride ourselves on being technical experts and on working in an inclusive and welcoming environment. And yet, the numbers don’t lie: of forty programmers, just four are women. What’s more, all of the technical lead positions in the company are filled by men.

It probably doesn’t look good to the outside observer. These numbers are even lower than data showing that women make up less than 20 percent of U.S. tech jobs, or that women hold 5% of tech leadership positions. There may be geographical factors at play, as we are based in Poland, but the figures still don’t look great. And yet we see ourselves as great supporters of women in tech, even if others might roll their eyes at the suggestion.

What is the case for our defence? In all honesty, it’s not a very complex one. When we advertise positions, we sometimes have one or two female applicants out of fifty responses — sometimes we have none at all. That leaves us with a question of integrity: we want to employ women, but we also want to employ the very best candidate every time. All things being even, the chance that the woman is the best candidate out of fifty applicants is about 2%. Do you choose a female who is perhaps the fifth or fifteenth best applicant just to fill a quota, or choose the best person regardless of sex?

To be clear, hiring a woman because she is the best candidate isn’t positive discrimination; that is just good business sense. And when we talk about the best candidate, that does not always mean the candidate with the most experience or the best qualifications. The right person is the one, regardless of gender, who we see growing and staying with us and bringing value to the things we create. It’s as much about attitude, personality, and ambition as it is about skills on paper.

Thomas Buberl, CEO of AXA, recently announced that “we have decided to reach gender parity in our top 150 global executives by 2023 at the latest.” On the face of it, it’s a noble cause; but does it mean removing experienced men from positions to replace them with women? Is positive discrimination the answer to the problem? We’re not finding fault with AXA’s approach; it just highlights that each business needs to make its own decision about how to handle the gender imbalance and stick to its own principles.

In the case of AXA, they are a global corporation with a massive talent pool to draw from. For us, as a small company, we can only interview and assess the people who are put in front of us. The failure to get more women into technology is not caused by businesses consciously choosing males over females; the problem is with the system that fails to turn young girls who show an interest in coding into women who enter the job market as qualified information technologists.

Girls show an interest in technology at around age eleven but usually move away from it soon after, a fact that is proven by the statistic that only 15.8% of undergraduates in STEM subjects are women. In fact, PISA found that by age 15 boys are ten times more likely to expect an ICT career than girls.

In PwC’s report “The Female Millennial — The New Era of Talent,” researchers found that young women want to work with employers with a strong history of inclusion, diversity, and equality. Many women see the low number of females in tech and simply choose to enter other fields. Essentially, there needs to be a breakthrough with more young girls choosing STEM subjects, so that they can then mentor and inspire the next generation. But creating that first wave of interest to get a really significant number of women established and visible in STEM careers is the major challenge.

The polemicists out there might ask if it actually matters. Tech is working, so why do we need more women working in tech? It is an somewhat unproven theory, but all the evidence points to the fact that any industry that has more gender parity and diversity of ideas and opinions will experience greater growth and success. This does not only mean more women, it means a range of ages, backgrounds, ethnicities, and opinions. Moreover, as we move into the AI era, diversity of ideas becomes essential to eliminating potentially harmful data biases — as explained by Beena Ammanath, VP of AI at Hewlett Packard Enterprise and founder of the non-profit Humans for AI.

So we’ve reached that point: we would like more women, and we even need more women on board, but the pipeline is not producing an even flow of candidates of different genders. We still see ourselves as supporters of the cause of women in tech, not because we employ a great deal of females, but because we are actively engaged in grass-roots organizations and causes that are trying to affect positive change for the future.

We’ve been active supporters and contributors to Django Girls for a number of years. Through mentoring at local events, we’ve seen how weekend workshops can help women of all ages build their first websites and fall in love with coding.

There are also a whole range of other female-focused initiatives around the world aimed at either getting girls into coding or empowering them once they reach the industry. Here are just a few:

• TechGirlz has run workshops for over 10,000 girls in middle schools in the US since 2010, and aims to double that number by 2020, while Girls Who Code have a network of volunteers running nearly 500 weekly coding clubs for 6th to 12th graders across the US.
• Technology association CompTIA launched a global tech career directory for girls and women aimed at helping them advance in the industry.
• Geek Girls Carrots, which started in Poland and how operates globally, has held over 500 events for 12,000 participants since 2011, bringing women in the tech industry together to inspire and assist one another.
• These grass roots initiatives are also prompting larger organizations to take action, with Sky offering a free 15-week starter-course for women in the UK with no coding experience to get started in a tech career.

We have a problem with the lack of women and other minority voices in our company. It is not the way we want it to be and we are not the only ones. Perhaps it is not something with an easy short-term fix and pretending that it is will not help anyone. However, we really believe that initiatives to help young girls see the value in IT careers will make things better. Is it a five-year prognosis for change? Ten? Fifteen? Nobody knows. But we hope change will come.

For now all we can say is that if you are a woman and you think you would be the best candidate for a role working with Python, Django, GraphQL, React or Javascript, we want to hear from you. Help us make that change and contact us at hello+careers@mirumee.com

We love to hear your thoughts on our thoughts, so please leave a comment.

Mirumee guides clients through their digital transformation by providing a wide range of services from design and architecture, through business process automation to machine learning. We tailor services to the needs of organizations as diverse as governments and disruptive innovators on the ‘Forbes 30 Under 30’ list. Find out more by visiting our services page.

A note from the writer: I don’t normally feel the need to put disclaimers on what I have written, but I do see the irony in being a man writing about the lack of opportunities for women. Copywriting is a much more equally represented area than technical positions; it just so happens that I am the only writer here but there is generally much more diversity in marketing roles. In writing this article, I spoke to women inside and outside of our company and listened to their feedback during the review. I’m the best choice to write the article, as that is my position in the company, but I believe that my words are endorsed by the women we have on board.

What’s the main takeaway?

• GraphQL is now a developer mega-trend
• Major industries are taking notice of the technology
• The language is moving into a new phase of maturity

On November 7–8, three of our team made the long trip to San Francisco for the GraphQL Summit.

As we have transformed Saleor into a headless e-commerce solution using a GraphQL API, and we have recently launched our new Ariadne library for building GraphQL APIs, we are pretty much all in on the technology as a game-changer for the coming years — meaning we just had to make the trip to the US.

Was it worth the jetlag? You bet. We got to hear talks from AWS, Apollo, GitHub, Netflix, and Braintree, among many others. More than that, we felt the energy that has grown around GraphQL over the last couple of years, which has now transformed from enthusiasm for an emerging technology into confirmation that we absolutely chose the right path when we decided GraphQL was to be the driving force behind Saleor 2.0.

GraphQL is a mega-trend

We usually start these round-ups of events with a summary of some of the great talks. That will come, but there is no denying that the main story coming out of the GraphQL Summit is GraphQL itself.

Since the stable release in October 2016 the growth has been incredible. In fact, it is absolutely no exaggeration to say that GraphQL is a developer mega-trend, as Apollo pointed out with this graphic:

Client downloads have grown from 10K a week to nearly half a million in the space of just two years. There has been an absolute explosion in interest for GraphQL and that also translates into the way people are talking about the technology.

Even in contrast with our experience in Berlin just a few months ago, people are no longer talking about implementations, they have shifted to discussing best practices. If there is ever a sign of a technology maturing, it is hard to find a clearer one.

The other indicator that GraphQL has rapidly matured is that we met people from companies like Sony, BMW, and Electronic Arts who had taken the time to be there and are seriously interested in what is happening. These companies are not traditionally ‘web apps’, so it is an important statement that they are taking notice.

Enterprise-level GraphQL implementations

Our feeling that GraphQL has moved firmly into the commercial space and is not just a technology for disruptive startups was confirmed by Felix Willnecker, a software engineer at BMW. He gave an interesting talk about how BMW internally uses GraphQL to create a single access layer for data coming from multiple sources such as databases, REST and SOAP APIs, including signals from millions of cars. His talk shows that GraphQL is not only for web apps and is being adopted in large enterprises. We might also be lucky enough to learn more about the results of their work, as Felix suggested to us that he might pop up at next year’s summit with a follow-up talk.

AWS has joined the party

From the technical side, Rohan Deshpande, Principal Engineer at AWS Cloud, showed a number of practical strategies on how to implement query bounding mechanisms. Limiting access to an API’s resources is one of the common issues that every public API has to face in order to protect itself against potential abusive requests. His talk was a signal that tech companies such as AWS care about GraphQL and want to engage with and contribute to the community by sharing their experiences and know-how.

Magic in front of our eyes

Perhaps the stand-out talk of the week was given by Adam Neary, Tech Lead, Web, at AirBnB. If we are honest, it probably wasn’t for everyone; it moved fast, took some giant leaps, and was pretty complex. But even if some couldn’t follow every twist and turn of the story, Adam is so funny and engaging that it didn’t seem to matter.

In a nutshell, he demonstrated the power that GraphQL provides to front-end developers, effectively giving them a lot of freedom by decoupling both back-end API implementation and UI. By building a fully-operational mockup of a website under 30 minutes, he proved that GraphQL is not only a convenient query language but also a modern and mature ecosystem that increases productivity for developers.

We got some time with Adam after his talk and he promised to write a short blog summarizing his talk for those who had missed some of the elements. Just a gentle reminder, Adam, we are still looking forward to reading that… :)

Taking time out from the talks

We spoke to Felix Willnecker after his talk and were excited by his enthusiasm for the technology. It was also great to chat to Tim Hingston, Frontend Tech Lead at Apollo, who showed us one of the newest Apollo products, the Apollo Engine. He shared our opinion that there is so far no satisfactory tool for supporting Python in the GraphQL community and was really interested in what we are doing with Ariadne, which was a big boost for us. We don’t always seek the blessing of people in the industry for what we are working on, but it is always really great motivation when people whose work you respect agree that you are heading in the right direction.

And that was GraphQL San Francisco. But before our 15-hour flight home to Poland, there was one thing left for us to do…

Lastly, thanks to the organizers for putting hosting a great event. The location was ideal and they really put together an exception bunch of speakers from across a range of industries and areas of expertise. It was everything we hoped for and more.

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