Enter the next Dimension…

…of Customer Engagement!

Oh no, marketing blabla!! … Pfff, so what. This prototype is cool enough to take it! Well it probably is… will be… okay, we still have to build it. But it will definitely be ready for the SAP Hybris Summit!…we guess. It all starts with this box:

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Inside it is not our new prototype but an essential piece of machinery belonging to our new partners NavVis. It’s an M3 Mapping Trolley used for “easy and fast 3D mapping of entire buildings in photorealistic quality.”

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It was fast and also very easy. That’s why Max was allowed to have a go…

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We had our Labs Innovation Space scanned and will create some kind (TOP SECRET!) of virtual shopping world integrated with Hybris YaaS. Again, visit us at the Summit to see the real thing for the very first time! To give you a taste here’s a link to a demo showcase provided by NavVis.

Bullseye – in-store targeting and analytics – an update

Yes, it’s more than  a month ago since the last update. The assumption was right – tons of work was ahead of us. And still things need to be optimized, beautified and fixed… but an end is in sight! We’ve made huge progress… we got products, we got a name, we overhauled the technology and worked with the designers to beautify the whole prototype. All while maintaining full YaaS compatibility and flexibility.

IMG_20151214_144959#1 – the name:  bullseye. We think it’s great for a prototype about in-store targeting and analytics.

#2 – the products: we switched from perfume to candy. This morning, I got the confirmation for >180kg of candy delivered next week to the hybris labs premises here in Munich 🙂

#3 why do we need all that candy? At this point, we also got full confirmation to make this prototype the central piece of art/technology at the hybris summit 2016. We’re running our recommendation and analytics system for two days at this event. If you can, please stop by!

In case you’re completely unsure what this is all about, here’s a brief summary – directly form the documentation that I’ve written yesterday.

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So let’s take a more technical view on the updates. Below is the current arch diagram, also soon to be even more shiny. For now, all technical goodness is on it. Let’s step through each part.

Bullseye - plat Technical Architecture (1)

platforms

bullseye is a YAAS-based in-store product recommendation and analytics system. The end-user facing and visible components are the platforms (here numbered from 1-8) that can be programmed via commands in various ways. For product selection, for example, the platforms may receive color events. The platforms also contain one or multiple sensors whose values can be requested. For power supply and communication, the platforms are connected to a base station via a standard Micro USB cable. As a typical IoT edge device such as a Raspberry PI has only a limited number of USB ports and limited power supply, standard USB 2.0 hubs are used in between the base stations USB ports and the platforms.

Recent updates here, not including bug fixes:

  • We’ve optimized the serial communication – previously all commands sent to the platforms (serial, byte-based communication) responded with an event that repeated the data for confirmation. We’re only responding with a JSON-formatted response in case the command triggered an EEPROM update or a sensor reading.
  • We’ve implemented new commands, mainly for light effects. The platforms can now flash in RGB colors (random flashing, simulates a “thinking” system” and a few other color effects.

Next, the base station – that’s where the platforms connect to via USB cable:

The base station is acting as a gateway between the platforms and the internet. It connects to the internet via the IoT standard protocol MQTT and to the individual platforms via a serial, byte-based communication protocol. The base station is subscribed to a MQTT topic for the base station itself and issues commands that are sent to this topic to all connected platforms. At the same time, it is also subscribed to individual topics for each platform – this allows each connected platform to be addressed individually. The central communication broker in this system is a MQTT broker. It is the essential element that connects the base stations to the internet and allows the remaining bullseye system to send commands to the platforms and to receive events from them.

Recent changes:

  • We can now address the base station itself with a dedicated MQTT topic and the base station forwards the command to all connected platforms. This minimizes the network load and is great in combination with the “flash” command. We use this command to simulate a thinking system, right before the results are presented with individual lit-up platforms.
  • MQTT reconnect behavior: we’v fixed a major bug around the reconnect behavior. From time to time, our MQTT connection is closed due to network issues. We’re now able to subscribe to all platform topics so that the system stays fully functional.
  • Our base stations are now Raspberry PIs and we use the excellent forever-service to start our node process in a “forever” fashion. Even if the process is killed, forever restarts it immediately.

Let’s move on to the bullseye YaaS package:

The bullseye package is part of the YAAS marketplace and can be subscribed to by a client project. The package contains the bullseye service, offering various UIs for the end user and retailer, and also the central matching service.  The matching service is a completely tenant-aware service, that uses the profile input from a customer questionnaire to score a selection of products. The result is a scored list of products that are mapped to platform IDs and then addressed with a color command over MQTT. This results in a physical selection of products based on a previous product matching algorithm. The bullseye service also contains an internal analytics module that is powering various analytics UIs. The bullseye builder module is used by a client project to configure the bullseye system. Typical configuration includes the mapping of products to platforms and the setup of a customer-facing questionnaire with scoring information for each correctly answered question.

Changes, well, tons. Let’s see:

  • The matching service is the central component, taking the profile info and matching it with products based on the questionnaire and scoring information. We’ve now implemented a proper blocking behavior – a user enters a session and operates the base/shelf alone for 30 seconds. If he chooses to keep using the shelf, the session is extended.
  • We’ve created 3 analytics screens that connect to real-time data via socket.io channels. All analytics is in memory, which is OK for a prototype. It’s nicely part of a single node.js library and could easily be persisted. Below are some of the analytics screens. More later on when the screens have been completely redesigned.
  • The questionnaire / form UI is already beautified. in the pics below, you see the result. It works excellently on desktop/tablet/phone, fully responsive. Form resubmission for flashing effects and the back button to play again complete the changes here.
  • A product info screen, connected to live product liftups, has been added.
  • A randomizer feature will perform a slideshow among the 3 analytics and product info screens. For events, we’re able to launch it and it just runs and shows all screens over time.
  • More… but this is getting too long…

So – you probably want to see some pictures, right? See below. What’s next? While a lot has been done, we’re still working on finishing touches. Potentially we’ll save the product results to a customer’s cart – so when she opens the cart later at home or at the event, the cart is prefilled with the matching products. We also need to take care of all kind of UI related small issues and we need to make sure the logistic for the hybris summit are taken care of. We’re creating an amazing construction, a pole-like art installation, together with our booth builders here in Munich. Stay tuned!

The state of the end-user questionnaire UI:

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The state of the builder module:

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And finally some of the early analytics screens:

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In-Store Targeting and Analytics – on YaaS!

It’s finally time to write about a new project we’re working on. Hopefully this also helps to clear up a few open issues we’re still working on. So here’s some news about a project we’ll probably name “bullseye”. To some degree it is an extension of the wine shelf. But it’s super flexible in terms of configuration and products. And – boom – it’s almost 100% based on YaaS, the new hybris commerce APIs.

Architecture, rough… 

This architecture is rough and can change any moment, but it’s a good ground to describe what this is about. The idea itself – again – is about selecting products in the physical retail space. And also about providing feedback to the retailer about physical interactions with products. YaaS plays a big role as we use the YaaS Builder Module system to edit all the configuration of the system. We’ve also written our own YaaS service, that provides the product matching logic in a completely tenant-aware fashion.

Bullseye - plat Technical Architecture (1)

Platforms and Bases = Smart Shelf

From a technical perspective, the hardware used is less impressive. It’s really not the focus this time. We’ve worked on a 3D-printable design that contains the electronics for the hardware parts of this prototype. Each of the platforms below (so far we have about 20 fully working platforms) contains a microcontroller for the logic, a large 24 NeoPixel LED ring (output) and a LDR (light dependent resistor, input). The platforms connect via Micro-USB to a base (power, serial data), which most likely will be a Raspberry PI again. In between, we need standard USB 2.0 hub, as  a Raspberry PI has only 4 USB ports and we would like to power as many as 20 or 30 platforms from one base. Check out some images below.

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The firmware that runs on the platforms is able to receive a few commands over a custom serial protocol. Via this protocol, we can change the identity of the platforms (stored in EEPROM), read the sensor value or issue a light effect command (e.g. turn all pixels on, turn them red). It’s a fairly low-level, basic, communication protocol. The only business-level logic that so far still runs on the microcontrollers is the calculation of liftup times. We count the duration between the increase of light (product lifted) and the decrease of light (product down). To not interfere with the NeoPixel (light) ring, we’re blocking the event calculation during the light effect execution.

The bases, most likely Raspberry PIs, each have a unique ID. The platforms, again, have unique IDs. Via MQTT (node.js using MQTT Client Software) we can issue commands to the bases and to the platforms directly.

MQTT Broker

An important architecture component that we can’t live without is the MQTT broker. Due to port restrictions and other technical issues, this part is currently outside of the YaaS cloud. For now, the bases connect to the broker to connect the platforms over serial. The bases subscribe to MQTT topics that match the platform ids. They also subscribe to a base-level topic, so we can send base-wide commands. If a platform disconnects from a base, we unsubscribe from the MQTT topic of that platform. This ensures that the communication bandwidth required is lightweight.

YAAS Builder Module

The builder module that you get once you subscribe to our package in the YaaS Marketplace allows you to configure the physical mapping and the questionnaire that the end-user finally gets to see. The products derive from the products you’ve configured via the YaaS product service. Below are a few honest screenshots, before we even started styling these screens (be kind!).

As a user, you’ll first have to choose a shelf, which is identified by the id of the base. Next, you choose which product category you’re creating the recommendation system for. All products of the shelf need to adhere to a common set of attributes, hence the category. Third, you’ll assign the products of that shelf/category combination to platform IDs. Finally, the scoring configuration – which questions, which answers, which score per correct answer is specified. The scoring configuration is the key ingredient to the end-user questionnaire form. Once all four steps are completed, the retailer is given an end-user URL that can be turned into a shelf-specific QR code (or put onto an NFC tag, or put onto a physical beacon or shortened and printed, etc.).

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YaaS Matching Service

Our matching service is triggered by a special URL that goes through the YaaS API proxy. All requests and bandwidth is counted and can later be billed. The end-user experience begins with a rendering of the questionnaire. The user chooses his answers and sends the data off to the matching service. The matching service now pulls the scoring configuration, the products and the mapping to calculate the matches. Based on the relative threshold, we calculate which products and therefore physical platforms are highlighted. Now, MQTT messages are sent out to the bases/platforms to highlight the appropriate platforms.

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Once a customer uses the system via a questionnaire, the shelf belongs to her for the next moments. This means we block access to the tenant/shelf combination for some time. During that time, the user is interacting in a personalized session with the shelf. Lifting up a product results in the display of detailed information directly on the customer’s tablet or smartphone. And of course, it fuels a few analytics displays that still need to be detailed.

What’s next? tons of work ahead.

We’re working hard on the specs for the initial version of this prototype and some sample products, categories, configuration that we’ll use for the hybris customer and partner days in Munich 2016 (early February 2016). But we’re also thinking of a few extra features that might make it into the prototype by then: for example, we’re thinking of a stocking mode, in which the platforms highlight one after each other and the screen shows you the product that needs to be on. It helps both the labs member to setup a demo as well as the retail employee to stock a shelf. And we’re thinking of sending the recommended products via email. A customer could then continue the shopping at home which a pre-filled cart.

Got ideas? Let us know. This is the time to provide input!

It seems Lars lost his brain – in Future

During Oktoberfest many people lose something like an umbrella, a shoe and control. But it seems Lars lost his brain that lies on his desk with some LEDs under it.

“Lars, is this your brain?”

“No, Lars, this is not our brain, it is just some slimy gimmick, which looks like one. I’m fine, don’t worry.”IMG_0433

“And why are there LEDs under it?”

“This whole thing is a prototype for a project. First of all I’ve connected a group of three LEDs and let them fade and pulse. The next thing was to control it with my Laptop. Therefore I’m using the USB connection to the Arduino and send the CPU idle time of my Laptop as numbers. The more my computer thinks the faster the brain pulses.”

“Can you say something about the project?”

“Yes, but we can also time travel to it.”

“What? Do you think we can time travel?”

to be continued…

How do you fit a bedroom into a shopping cart?…

…or a kitchen? …or a garden? Answer: you don’t. Our next prototype is coming soon! Here’s a short preview:

It’s going to be a prototype for any scenario within which the customer is not able to put the items of interest into a shopping cart or basket. Either because they’re too big, or too heavy, or the items are only samples in a showroom. You could also imagine a B2B scenario. For example a cook of large-scale kitchen collecting ingredients from a wholesale market. The idea behind “Infinite Cart” is that the customer does not have to make notes, or take photos of the potentially desired products. Instead, all the required information will be stored on a device we’re just building ourselves.

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As you can see, it’s a wearable…will be…sometime…perhaps… In any case, there’ll be some flashing LED’s. Oh, and we’re resurrecting NFC. Apart from all of that it’s going to be integrated with YaaS.

If you have any ideas or suggestions, please contact us!