Drapers reveals the Israeli retail tech start-ups ready to inject innovation into your business.
Tel Aviv is a city with a mission: to challenge the dominance of Silicon Valley as a leading hub for the latest retail technological innovations. And it’s proving very successful.
Despite being Israel’s second city, after the capital Jerusalem, Tel Aviv is the epicentre of Israel’s tech boom. Located on the west coast, the city is home to thousands of innovative start-ups seeking to revolutionise the future of both in-store and online retail.
The British Embassy-led UK-Israel Tech Hub, which aims to support British firms in partnering with Israeli innovators, estimates there are more than 5,000 active tech start-ups across Israel, with the majority focused in Tel Aviv, making the country the world leader in terms of start-up density per capita. Identifying the potential within this relatively small nation, venture capital investment also stands at $170 (£150) per person, compared with $70 (£62) in the US.
Alongside these start-ups are more than 300 multinational research and development centres, giving Israel the highest rate of R&D spend per percentage of GDP at 4.3%. Again, most of these are focused in Tel Aviv, including tech giants Google, Apple, Facebook, Alibaba, Amazon and Microsoft.
With innovations including online fit solutions and the ability to track shoppers across devices and directly link products to emerging social trends, Drapers visited Tel Aviv earlier this month with a delegation of UK and German retailers – led by ecommerce consultancy Athito – to unearth the latest offerings. After attending a Dragons’ Den-style pitching session of more than 20 retail-focused start-ups, here are the top 10 that fashion retailers should know about:
Helping retailers respond in real time to emerging social media trends, Mmuze uses in-house algorithms to match a retailer’s full inventory to developing trends, enabling adverts for those items to be targeted at the relevant demographic. So if a celebrity tweets about a black dress she is wearing and a buzz is created around it, Mmuze can locate a similar dress in the retailer’s catalogue, identify the core market for this trend and promote automatic adverts to that specific audience. “We help retailers get in front of the right audience when they are emotionally ready to be engaged,” explains Ran Zfoni, co-founder and CEO. The retailer just has to define the advertising budget and period for the project to run but can also control the generation of adverts once a trend has been spotted if preferred. Mmuze has already run a three-month test with Ebay and is now working up plans with a number of unnamed international and UK retailers. The firm, which is currently focused on Facebook, is also extending its technology – reliant on supervised machine learning rather than keywords – to reach audiences within retailers’ apps and on Twitter.
Gareth Rees-John, Topman’s digital director, says: “Spotting a buzz across social can be hit and miss. I think it’s easy in the area that they showed (make-up), because it’s easy to have a similar product. It’s much harder when it comes to fashion trends as they could be described in many different ways. The second challenge is the product feed that drives the recommended products; feeds are notoriously inconsistent and for a single brand you may not have many products that match the social buzz. I liked the application in Facebook where you could produce an ad matched to buzz.”
James Doyan, managing director of Athito Retail, says: “The concept is solid if not unique and hinges on the retailers’ ability to react to trends in real time which can be quite a challenge on top of other market forces.”
Attempting to solve footwear retailers’ frustration in providing accurate size guides online to reduce returns, Fitfully enables shoppers to create 3D scans of their foot which can be virtually inserted into shoes. Shoppers place one foot on a piece of newspaper and, using a smartphone, take a video circling it. Fitfully’s software – which can be embedded onto retailers’ product pages – creates a model of the foot using 25,000 measurements, which is aligned with a virtual version of the required shoe. The shopper is shown three sizes that are a close match to their foot, coloured in green to show where the fit is good and red where it might be too tight, enabling them to select their preferred fit. It is accurate to within 1mm. Roy Tertman, co-founder and chief product officer, says Fitfully is working with Adidas to launch the technology, as well as with shoe manufacturers to build a 3D last fit database.
Sean McKee, Schuh’s head of ecommerce and customer services, says: “What is different about Fitfully is the extremely physical use of the phone in the customer’s hand, making an arc around the leg, referencing physical objects and brand archive to offer the best size for the customer. Complicated, yes, and reliant on brands being happy to share assets, but perhaps sufficiently intuitive to be on to something.”
Aiming to banish the “No results found” page, Cymbio provides shoppers with an alternative when the product they want cannot be located on a retailer’s website. CEO Roy Avidor explains that it “virtually extends catalogues, giving shoppers an endless aisle experience” by presenting similar products from the original retailer or the exact product on another site. If the shopper opts to buy the same product elsewhere, the retailer benefiting from the referral will pay for the lead, which is split between Cymbio and the original retailer. Retailers can ban rivals from appearing on their site and can control the ratio of their own similar products versus exact matches offered elsewhere. With up to 25% of searches returning no results and 75% of those shoppers then likely to abandon the site, Avidor believes Cymbio will help retailers retain shoppers or monetise this situation, and enable smaller retailers to better compete with larger players.
Adham El Muntasser, Zalando’s head of mergers and acquisitions, says: “This is a good idea as it gives online shops the chance to make themselves bigger than they actually are by showing the customer a wider range of relevant products. In the best case it will be perceived by customers as a positive effort by the shop and thus increase loyalty. Loyalty could however suffer if the customer is often directed to the same alternative shop.”
Zeekit uses technology originally developed to locate and highlight missile launchers on radar images to help women virtually try on clothes. The software enables shoppers to take full body pictures of themselves and superimpose onto them items of clothing in the right size. Each product is broken down into 80 sections, enabling it to be matched closely to the body. It is currently focusing on the business-to-customer route by testing an app, likely to be launched for Black Friday, enabling shoppers to browse a retailer’s catalogue by swiping up if they like a product and want to try it on. Co-founder and CEO Yael Vizel says it has been tested with 12,000 shoppers and one in 10 clicked through to retailers’ product pages, while one in six shared images of them ‘wearing’ the item. Once an image has been shared, those seeing it can also try on the product, creating the potential for items to go viral.
Sean McKee says: “‘Zeekit’ is Hebrew for ‘chameleon’ and the software aims to be a one-stop shopping revolution for time-poor digital fashionistas. Like all apps, it will need download volume and relevance to create momentum – and most importantly, to persuade shoppers that staying away from the shops can be just as much fun.”
Donde provides a mobile search platform that enables shoppers to find products based on their visual characteristics, including neckline, sleeve length and colour. Suited to retailers with a deep product catalogue, founder Liat Zakay says it can be used to find any product in just 15 seconds without the need for uploading images, which can be poor quality. Donde, run as an affiliate site but with the ability to be embedded into retailers’ own systems, allows shoppers to filter their search by brand, retailer, price and sale status, with purchases from retailers made in just two clicks. Items can also be saved to a wishlist with shoppers notified when they go on Sale, and the tech learns shoppers’ preferences displaying results that best match their style.
Gareth Rees-John says: “This offers a really well thought-out customer use case and journey. I felt it was a commercially viable tool that women would really use. But it would only work on an aggregator site or marketplace, as on Topshop, for example, you would only return a few products after you had filtered a number of style choices.”
James Doyan says: “Donde is a clever tool that scrapes the web for product that has the attributes the searcher is looking for. A completely new way of searching, it is intuitive, simple and promises to find the product required in 15 seconds. Worth considering.”
Aspectiva enables retailers to capitalise on increased sales when utilising user-generated reviews, even if shoppers are not forthcoming with this content. The technology trawls the web to find reviews hosted elsewhere on the same product and displays sections of those on retailers’ websites. These can then be searched using buzzwords so shoppers can find comments that specifically relate to its use, for example as sportswear. Complementary products are also displayed alongside the original item. The technology is already being used by Shop.com.
Adham El Muntasser says: “The trick here is the comprehensive aggregation of reviews and a smart categorisation. The greatest worry would always be quality assurance. It’s very important that the algorithm ensures high product relevance and cuts out inappropriate statements. It’s particularly interesting for smaller shops; for larger shops it might not be a major value-add.”
Awear Solutions (awearsolutions.com)
Liron Slonimsky has devised a small chip that can be inserted into garments indicating to retailers when items are worn and in what type of location. The chip, synced with an app on the shopper’s phone, triggers rewards to be sent when a product is worn. Slonimsky stresses that retailers are unable to receive personal information about shoppers’ movements as all data obtained is encrypted and tags can be turned off at any point. She says: “Usually shoppers get nothing for presenting brands. With Awear, shoppers get rewarded for wearing an item and being the brand ambassador.” Shoppers can share when they are wearing clothing, increasing brand visibility, and if a product is worn near the store the app can send push notifications with rewards and recommend complementary items. Three unnamed US brands are working with Awear, specifically for handbags.
Sean McKee says: “While on first glance this might look like the internet of things gone mad, the group could see some potential use cases, such as a luxury handbag where the tracking might work well with customer expectations of a relationship with the brand. For the mass market, Slonimsky needs to work out what the incentive is for the retailer to effectively extend product lifecycle, and pay for it, and for the customer to trade their privacy.”
Tackling a key issue for many retailers – tracking shoppers across multiple devices to fully understand shopping journeys – Crosswise thinks it has the answer. Using its own in-house algorithms, the start-up sifts through online usage data, matching up use patterns to prove two devices belong to the same person, offering a retailer cookie IDs for the different devices. No personal data is provided to the retailer, just the fact that the devices are owned by the same people. Retailers can then look at their own data to decipher what the shopper has been looking at to better target advertising at them and personalise experiences across devices even when they don’t log in. Steve Glanz, co-founder and CEO, says the firm launched in the UK this summer and has an 85% accuracy rate. It is already working with retailers such as Shop Direct.
Gareth Rees-John says: “The biggest challenge for multichannel retailers is cross-device matching. Without universal logins or cross-device cookies, it’s impossible to match up journeys. I would love to see what this data looked like for Topman. One thought though: this is a very grey area of data privacy. I think that it will be closed off before long as it’s basically spying on users. It would need to be totally anonymised data and therefore only show trends, rather than actual users, making it good for building business decisions, but not for personalised messaging.”
James Doyan says: “Consumers shop across multiple devices and their activity is normally only tracked at device level (unless they are logged in to a site). Crosswise detects activity across devices and enables retailers to retarget to specific customers with an 85% accuracy of cross platform identification. We liked this tech a lot.”
This firm, which is already working with the likes of etailer Shop Direct and voucher site Groupon, enables multi-brand retailers to offer their brands sponsored product promotions – bringing in-store shelf positioning merchandising to online. Brands bid to appear in the sponsored space, which can be embedded anywhere on the retailer’s home or category pages, and Mabaya automatically pulls in the highest bids. Co-founder and CEO Avi Rabinovich says featured brands can expect an average sales uplift of 23%.
Adham El Muntasser says: “This provides a highly relevant service for larger ecommerce shops that see lots of non-converting traffic from users far progressed in the ‘purchase funnel’. It is valuable for brands to reach users exactly at the point when they are ‘consuming’ their respective product categories. However, the retailer needs to be the point of reference for customers in the given category so it’s worth the effort for brands to run specific ad campaigns there.”
Aiming to revolutionise advertising, Mobilibuy enables retailers to make every advert – whether on a billboard, on TV, in a magazine or on a bus – instantly shoppable, without the use of difficult-to-scan QR codes. Chief technology officer Ziv Kitlaro explains the start-up uses image recognition so when a shopper goes into the app and scans an advert the particular product is instantly recognised and the shopper is directed to the retailer’s relevant product page. Voice recognition can also be used to describe the product in the advert. Kitlaro says once retailers have uploaded their catalogue to the system, the tech will “enable retailers to open virtual stores anywhere and bring the store to the traffic.” The technology has already been put to use by Chelsea Football Club to enable match day football fans to buy from the programme, as well as by Unilever and Kraft.
Gareth Rees-John says: “I think this will become a part of Google in the future, to be honest. The difficulty is getting the user to download another app; they are not going to do this unless there is a group of advertisers backing it, for example an agency that owns all the bus stop poster sites across an area.”
James Doyan says: “This is a mobile app powered by image recognition that enables one click purchasing. Whilst smooth and intuitive, there are other equally impressive products on the market so for this to succeed marketing for awareness is critical.”
To read a comment from Avi Cohen, digital solutions manager at the UK-Israel Tech Hub, click here.
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