Get ready for Summers top trends.

Get ready for Summers top trends.

(image credit: Aje)

Summer is days away and there is an optimistic energy in womenswear this season.  The key trends your customers will be searching for online include silhouettes that emphasise drama and volume; think statement shoulders, deep V necklines, rising hemlines and mini dresses. ‘Romance’ and ‘Safari’ looks are also strong trends this season. Read below for our word tag suggestions!


Make sure your key word tags include the one-shoulder dress to pick up on this seasons hottest trend! This Summer it’s all about the shoulders, either bearing them with off the shoulder styles, or decorating them with puff sleeves or bow detailing. 

Tops and dresses with shoulder ‘puffs’ or ‘blouson sleeves’ are growing in popularity, with Google Trends experiencing search volume growth for ‘puff shoulder tops’. Ensure these key words are attributed to any items featuring these details.


Romantic looks continue to appeal in Womenswear, with many retailers giving us beautiful feminine blouses in light and textured fabrics, with blouson sleeves, shirring details, in florals and paisley prints. As customers become familiar with this look, be sure to tag words such as ‘sheer’ to capture those looking for these feminine styles in light floaty fabrications. 

The ‘bias satin skirt’ continues it’s popularity for another season, updated in this Summer’s hottest colours and prints.

Driven by trends for whimsy and fantasy in occasion wear, ‘fabric bow’ detailing is up-trending as a shoulder detail or cinching in waists. Feature bow details appeared on the recent global catwalks and on the red carpet at the 2019 Emmy awards, further confirming the trend and adding to it’s retail appeal. Tie your look together with a statement bow!

(image credit: Zimmermann)


The ‘Linen Blazer’ and ‘Safari Jacket’ bring us this Summer’s relaxed workwear items. The ‘safari trend’ is a nice update for the customer whose style is more minimalist and pared back. 

The elegance of a Safari Jacket in crisp neutrals offers a chic workwear option, with details such as multiple front pockets and self-fabric waist ties. Paired with ‘paper-bag waist’ pants, skirt or short, these items create a relaxed and sophisticated look. 

Several Australian brands offer a fresh take on shirting, with cropped shirts, wrap styles in crisp cottons, and volume in the shoulder bring refreshed aesthetics to the basic work shirt.

Relaxed suiting in a soft palette of cream, olive green, soft pink, and terracotta in crisp fabrications is providing a refreshing option for workwear styles.

(Image credit Aje Instagram)

#MarigoldYellow #Pastels #Neutrals

Worn head to toe, yellow continues to trend in saturated hues. Customers may search using a range of yellow terms including ‘golden’ ‘marigold’ or ‘mango’ so ensure these tags are captured to help boost search results and sales.

Neutral and earthy palettes offer customers a harmonious palette in line with the relaxed linen styles. Earthy colours continue to trend with palettes featuring terracotta, cream, and shades of green. Layer them over one another for a pared back approach.

Customers will also be searching for pastel hues this summer, including blush pink, sky blue, and lemon.  Hot pink also looks fresher this season when it’s paired with red. 

#AnimalPrint #Spots #Paisley

The popularity of ‘animal prints’ continue this Summer. As this print direction gains traction and customers become more distinctive in their preferred animal print, we suggest including additional tags such as ‘zebra’ or ‘snake’ to your products.

Other print directions include palm prints and paisley prints which work back with this seasons overall ‘safari vibe’. Spots remain a strong pattern trend, as well as gingham which works especially well for resort wear and swimwear.  

Our top recommended word tags for Womens Summer apparel:

  • ‘One-shoulder’ dress or tops
  • ‘Puff’ sleeves 
  • ‘Safari’ suit or jacket
  • ‘Paper bag waist’
  • ‘Yellow’, ‘Mango’, ‘Marigold’
  • ‘Spot’ and ‘Gingham’ print
  • ‘Animal print’ ‘Snakeskin’ ‘Zebra print’

Fossick Trends is a marketplace where Designers can search and shop for on demand ready-made trend reports. Downloadable PDF’s covering Womenswear, Menswear, Kidswear, and Accessories.

For more information regarding Fossick Trends, Check out

Contact Lyndal Wallis:

10 types of content to increase eCommerce engagement

The way people shop for products has become a mishmash pathway, toggling between online and offline sources.  The customer journey is far from linear, which forces brands to be just as nimble in engaging with shoppers. It’s up to brands and marketplaces to create a variety of touch points and valuable content streams to encourage engagement, connection and loyalty.  

When marketers put themselves in their customers shoes and imagine their typical movements and actions, they can shift communications from being one-sided to conversational.  As brands develop campaigns with the intent to connect and engage, shopper interest increases.  

Sam enjoys the search of finding fresh outfits, not so much the shopping part as he prefers it to be timely and convenient. He follows his favourite brands on Instagram and Facebook and Sam is on several mailing lists due to previous purchases, receiving regular updates on new products and sales.  A typical day in Sam’s life, he wakes up early scrolls social media and scans emails, heads to the gym for an hour’s session, back home for breakfast and commutes to work.

After dinner one evening, Sam starts to wind down, falling onto the lounge for a few episodes on Netflix.  He has a quick thought about getting a new tank for the gym sometime this week, but being time poor with work he’s not sure if he’ll get to the shops.  Sam opens Chrome, a quick search for ‘men’s black tank gym.’ A few brands he knows show up, but there’s a new one he hadn’t seen yet – Brand X. A quick browse on site and he’s enjoying the styles, graphics and aesthetic of the website experience.  Without much thought, Sam is happy to pay $35 for a new gym tank opting to use Apple Pay, which makes things simple and easy.

As he’s waking up one morning, there’s a new email from Brand X, Sam glimpses new product drops and notices an article titled ‘The ultimate workout routine for men’.  Immediately capturing Sams attention, he already has gym on his mind and continues to read the article getting some awesome tips on improving his current routine.

man shopping online deliveries

That particular touch point is invaluable to building loyalty with Sam.  The brand is communicating with the intent of understanding the lifestyle of their consumers. For Sam, he feels like there’s more to be gained by opening Brand X emails with interesting articles aimed at helping him improve and excel in hobbies and interests he’s most passionate about.  

We’ve compiled 10 types of content for eCommerce businesses to implement that will not only increase engagement, but optimise organic reach across search engines.

  1. Unique product descriptions
  2. Image meta tags
  3. Website on page descriptions
  4. Social Media – image & text
  5. EDM’s – product updates sales, styling tips, news relevant to audience
  6. Customer reviews
  7. Youtube Videos
  8. Blog posts and interesting lifestyle articles
  9. Online communities
  10. Personalised thank-you notes

When arranging Sam’s day in a timeline of events, along with a loose customer experience map, brands can start to see how each touch point links to another.  The output is consistent brand messaging, enjoyable imagery and above all meaningful content that has a long-lasting resonance.  

Okkular Tag Gen uses image recognition technology to automatically attach tags to products based on patterns, colours and styles, making it easier for customers to search for the items they’re looking for.  Contact their team for a complimentary demonstration of Tag Gen.

Gamified Fashion Marketplace –, an Okkular Tag Gen Case Study

Key takeaways for using Okkular AI based Tag-gen solution

  • Over 8 weeks of full-time hours saved for tagging over 20k products. This helped in reducing cost and time significantly and go to market faster.
  • Produce over 20 product specific Tags/attributes for each apparel, which helped in making the search engine more efficient and robust
  • Over 80% accuracy on an average with AI classification and the ability to audit to make it 100% accurate 
  • Classify multiple colours which would have taken additional time and cost to add for every product manually. 

Intro to

Dresswhere is an upcoming aesthetic gamified search-engine for fashion. They don’t expect users to know what they want, so instead of asking them a very complex question (‘what are you looking for?’), they ask them a very simple question repeatedly: ‘which of these three apparels is best visually?’ Every time the user chooses an apparel or skips, they’re shown another three apparels that are slightly more specific to their tastes based on their previous choices. The effect is that, over the course of ~3 minutes, the user zooms in on an individually curated collection of apparels. Whenever they scroll down, they see their top results, and can click through to the retailer.

What was the pain point for Dresswhere to make the search engine efficient?

To create the Dresswhere search engine and predict a closer matching apparel, Dresswhere had to Tag every apparel’s image with at least 6-8 attributes/Tags. The catalogue inventory was over 20K products and requiring ongoing 3-4k products added every month. Dresswhere gets the product catalogue feed from multiple Fashion brands and the data received in the feed was inconsistent and was not enough for the search engine to work efficiently. While performing the task of tagging products manually, Dresswhere had two main issues.

  • Time taken/cost incurred to tag over 20k images and ongoing 3-4k products every month. Dresswhere estimated this would take approximately 9-10 weeks to tag over 20k products. 
  • The inconsistency and error rates

The above two issues were two key pain points to overcome for Dresswhere to successfully launch their product.

How did Okkular solve Dresswhere pain points? has developed an AI based visual analysis solution which helps in automating the product tagging process. The AI tool generates tags from just the product images in under 15secs per product, increasing the speed to over 15 times faster compared with manual tagging. The tagging process also helps in reducing errors, generating consistent data and significantly reducing costs. 

As an example, Okkular Tag-gen solution can generate over 12 attributes for a dress including key attributes like neckline, style, length, print and also tags for occasions and avatars. The tags generated can be used in many ways including, titles, description, filters, product specific keywords, and meta tags.

Dresswhere provided us the product feed in a google feed format and the output of Tags were uploaded by connecting via Okkular API to Dresswhere platform

Working closely with Angas (Founder Dresswhere), we were able to develop additional key tags which were very specific to Dresswhere. We also trained and generated over 20 tags instead of 6 to 8 which was an initial requirement for Dresswhere if the task had to be performed manually.

During this project we frequently received feedback from Dresswhere to improve the classification accuracy, user interface and additional features which helped us co-create a solution which has not only helped Dresswhere but many other retailers using our solution currently.

What are the benefits for Dresswhere? 

  • Over 8 weeks of full-time hours saved. This helped in reducing cost and time significantly and go to market faster.
  • Produce over 20 Tags/attributes for each apparel, which helped in making the search engine more efficient and robust
  • 80% accuracy on an average with AI classification and the ability to audit to make it 100% accurate 
  • Classify colours from Apparel which would have taken additional time and cost to add for every product manually. 

Okkular is also working with Dresswhere to provide Okkular Visual search solution to help their users find similar looking products from multiple brands once they have identified a dress, they want using the Dresswhere search engine.  

If you would like to learn more about Okkular solutions, contact 

Mahendra Harish: 

For more information regarding Dresswhere, Check them out at

Contact Angas Tiernan: 

Tips to help you improve product catalogue search and discoverability

Imagine this, Erin has a slight obsession with sunglasses. She already owns several pairs in various colours of similar style and shape because Erin knows what suits her face. She’s on a mission to find a chic pair of tortoiseshell sunglasses online and in a few clicks she’s landed on her favourite e-tailer site. Erin begins her search by firstly heading to the accessories menu, then into sunglasses. The excitement of an impending purchase is building.

That’s an impressive selection, 25 pages of sunglasses. Time is of the essence, she pans to the menu on the left to filter by colour and style. To her dismay, Erin can only filter colour and this leaves her with 400 products. This is not ideal as she knows exactly what she likes and scrolling through 12 pages is overwhelming and time consuming. The purchase inducing enthusiasm subsides quickly. Erin drops off the site and tries a long-tail keyword search instead on Google, which places her in prime position to find exactly what she’s looking for. She’s quickly matched with retailers who have their site optimised with clean content and relevant tags sorted.

94% of shoppers abandon a website or purchase when they are unable to find what they are looking for.

Generating product specific Tags creates a solid foundation of product data leading to benefits such as: improved on-site search, and search engine optimisation. Developing and maintaining product specific keywords results in a better user experience and increased conversion rate.     

88% of shoppers say that detailed product content is extremely important to their purchasing decisions.

We break things down into three tips, so you can get started on improving your product catalogue. Ensuring shoppers like Erin find what they’re looking for and keep that purchase excitement going.

Tip 1:  Amplify your content for better SEO and on-site search by including targeted keywords in product descriptions and relevant words in image meta-tags. This means shoppers using long-tail keywords in search queries will be more likely to see your products listed first.

Tip 2: Familiarise yourself with Google Trends and local search queries. Having a finger on the pulse in terms of real-time analytics of what shoppers are looking for, helps you to be dynamic in providing relevant product recommendations . This will also aid in keyword research, as trending products can change quickly and you’ll need to stay ahead of your competitors.

Did you know?
Manual tagging can take up to 30 hours for just 500 products

Tip 3: Switch to automated product tagging and create consistent product tags. This will cut down the time it takes to do the process manually and ensures all the words used to tag hundreds, even thousands of products is consistent. Tagging products manually is prone to mistakes, leading to incorrect data and a poor user experience.

50% of data workers waste their time finding and correcting errors or attempting to confirm data sources they do not trust.” Harvard Business Review has developed an AI based visual analysis solution which helps is automating the product tagging process. The AI tool generates tags for your products in under 15secs/product increasing the speed to over 15 times compared with manual tagging. The tagging process also helps in reducing errors, generating consistent data and significantly reducing costs. 

As an example, the solution can generate over 12 attributes for a dress including key attributes like neckline, style, length, print and also tags for occasions and avatars. The tags generated can be used in many ways including, titles, description, filters, product specific keywords, and meta tags.

Okkular solution is simple to use with these easy steps.

Step 1:  Upload your product images or Provide us your product feed. Get quick results.

Step 2:Review and Validate the AI generated tags

Step 3:  Download ready to use SEO-Friendly Tags or Automate integration using our API.

Let’s get started! Feel free to contact us for a free demo.

Understanding eCommerce product recommendation engines in fashion

The time to ramp up product recommendations is now in fashion, and why AI is at the core of personalised shopping.

Creating a personalised experience for shoppers is a sure way of generating repeat business, building brand loyalty, making better business decisions through product analysis and as a whole, increase business longevity, producing a healthier bottom line.

Melissa loves social media.  Her preferred platforms are Instagram and Pinterest.  She has dozens of Pinterest boards and hops in and out of the app daily, looking for inspiration pinning multiple styles that reflect her personality.  Instagram, for Mel is all about tracking the most current hashtags and following her favourite influencers and celebrities.

90% of Pinterest users say using the platform helps them make a decision to purchase something.

What Pinterest does really well is provide highly relevant content based on user data and search queries.  Continuously learning about a user’s profile and preferences, serving up only the most inspirational content.

Going down the ’More like this’ path in Pinterest is like watching the makeover scene in Pretty Woman.

Reading any current ‘Future of Retail’ report and there are typically three key concepts driving change across the industry – convenience, automation and experience.  These studies are supported by large consumer groups surveyed about their shopping habits. One very common response is that shoppers are absolutely more likely to shop with brands that provide them a genuinely personalised experience, 71% actually, in the recent PSFK Future of Retail report and Shopper Attitudes 2019 Survey.

These statistics are not surprising. And, as everyday people, we can also appreciate what it feels like to receive a personalised shopping experience.  However, the pressure is on those working in the industry to create personalised experiences in their own business. This is where an understanding of empathy, nurture and delight are critical and should be prioritised just the same as resources and budget allocated to acquiring customers.  Why? Because the result of being empathetic, nurturing and delighting customers will organically convert into brand loyalty and repeat shoppers.

Back to Mel for a moment.  She’s aware of the latest trends in fashion, doesn’t purchase unnecessarily and will take some time researching and making a decision to buy something new based on what she currently owns, loves to wear and matches her style.   Mel has interacted with various fashion sites recommending products while she’s browsing the site, however she doesn’t want to see what others bought with the dress she’s looking at. She’s different. Melissa expects, at a very basic level that her individual fashion preferences are taken into consideration when being recommended products to purchase.

Technology has become significantly smarter in the past 10 years with artificial intelligence now the bedrock of many programs.  A number of platforms having already integrated AI to their software without users realising, namely, Pinterest and Instagram.  This is largely due to an exorbitant amount of data generated online.  From clicks, bounces, double-taps, actions and purchases to capturing browser history, downloads, uploads, streaming and geo-tracking.  Big data, our digital footprint, the way we behave online is feeding AI systems all over the world. It’s then translated into insights from patterns and analytics, which can then be used to complement business intelligence and improve the user experience.

When it comes to shopping online, most eCommerce stores will have a product recommendation engine installed.  This software carries out one main task, to recommend additional product to a shopper as they’re browsing a website and product page.  There are three types of product reco engines:

  1. Collaborative filtering – tracks and groups other users actions to predict what another shopper will like.  
    1. Eg: Others also purchased these products with this item.
  2. Content specific – a profile is created by tracking website pages and clicks of that user and the profile is compared to a product catalogue to identify which products to recommend.
    1. Eg: Products similar to this item.
  3. Hybrid – a mix of both collaborative filtering and content specific.

AI driven product reco engines are more sophisticated in that algorithms continuously learn over time users personal preferences and show products based only on similar tag and attribute characteristics.  This form of recommendation outperforms generic engines because it is highly personalised and programmed to adapt to preferences. This is significantly more useful than the logic of comparing a shopper to a group or catalogue in that one online shopping instance.  

One afternoon, Mel is enjoying a coffee and taking a few moments to scroll through Pinterest and casts her eye across an advertisement.  The ad image is a dress similar to a few images she’s pinned to a recently created Pinterest board labeled ‘Special night out’. Mel clicks the ad and is taken directly to the dress listed on a fashion eCommerce site she didn’t know about.  She reads the dress description, and will keep that top of mind while she continues perusing the site. Mel won’t make a purchase just yet, but she really loves this site and starts spending more time on it looking at shoes, accessories and back to dresses.  Over the duration of a few weeks, Mel is ready to buy the dress and clicks back to the site. She notices the recommended products are actually items she likes, and hadn’t noticed the earrings suggested previously. It was without hesitation that Mel could envisage the whole outfit together.  The dress with those gold statement earrings and she would wear her gold strappy heels that she’s had for several years and have never failed her.

The power of a personalised product recommendation through AI in Mel’s experience isn’t the technology, it’s her imagination bringing the outfit to life.  Mel is different, and so is everyone else looking to be inspired to shop and regular product recommendation engines just won’t cut it.

Fashion retailers of all sizes can now access these engines economically and as a standalone software product that isn’t part of a convoluted all-in-one package.  The team at Okkular can look after the implementation, getting you setup with their AI product recommendation engine and get your business on the path to personalisation.

Increasing the discoverability of an online fashion business

Benefits of creating a digital presence for your fashion business, increasing the discoverability of your brand and in turn achieve organic growth.  

The fight for shopper acquisition is strong among fashion businesses.  Target audiences are bombarded with ads, remarketing and a constant stream of cart abandonment notifications.  When focus is heavily on the transaction, the opportunity to connect in the early stages of browsing is missed. To have a shot at building a relationship with a potential shopper, some dynamic content tactics need to be in play.

On her way to work, Lucy finds out her best friend Jess got the promotion she wanted and she would love to celebrate on the weekend at a newly opened bar.  Lucy replies with emojis and congratulations, she knew Jess would get it. But, what to wear? They hadn’t been out in a while and she thought something new would be nice to pep up her confidence.  She has a few days to find something cute, and so the inspiration stage begins.

In 2018, Salesforce and Publicis.Sapient published a fascinating report on customer behaviour citing a whopping 87% of shoppers begin product searches on digital channels.

This is why relevant content (text and image) is important in fashion. By ensuring topics and tags featured across a site are optimised for search engines, this will increase the discoverability of a fashion business and Lucy finds something stunning to wear for a night out.

There are a few foundational steps to increase the chances Lucy comes across an outfit based on her preferences and search criteria.  It’s important for retailers to understand what she is searching for and the language used, then fashion businesses can hone in on delivering relevant content to people in their target demographic.

No 1.  Establishing a digital presence in fashion

The fact that most people are starting their buying journey by searching online, shows it’s absolutely critical to have a digital presence. Only using social media such as Instagram or Facebook just isn’t enough.

Browsing typically begins with simple queries typed into a search engine.  In Lucy’s case she’s looking for something like, or is keen to be inspired by pieces that are categorised as ‘short glam party dress with one shoulder.’

Results are shown based on websites targeting specific keywords and upload original content and or products regularly.

Fashion businesses targeting keywords featured in the shopper query appear more prominent in the description. Encouraging a shopper to go directly to those websites, because #relevant. The likelihood of Lucy finding what she’s looking for is much higher than an ad promoting generic ‘dresses’.

From this point, she checks out a website and dives into browsing all the beautiful things.  The longer you can get Lucy clicking around a site, products, recommendations or perusing other digital touchpoints the better. This may include reading a blog, subscribing to a newsletter, scrolling Instagram and Pinterest.  Then the brand has a great opportunity at starting to build a genuine shopper connection with Lucy.

However, feeding search engines content they like is the next important part.  But, if cutting corners comes to mind by duplicating or copying descriptions, then just beware search engines have incredible algorithms separating the good from the not so good.

No 2. Optimising content for search engines

Search Engine Optimisation can be a hefty task to manage and a great place to start is by making note of 10-15 keywords in line with the business’s core product or service offering.  

Here is an example list for a multi-brand fashion marketplace – womens fashion, professional womenswear, nine to five, loungewear, athleisure, premium loungewear, luxury intimates, womens occasional, party outfits.

These are all pretty stock-standard keywords, however you can add long-tail keywords, which are bundled keywords in the shopper’s language.  The search query Lucy made previously makes up long-tail keywords.

Google Trends is your friend, get to know it well, it will help you greatly in keeping keywords on trend.

From there, generating descriptions for website pages and products communicate what a business does and what it’s selling.  Search engines scan for these descriptions and load as the text under website results. See below as an example.

No 3. Helping shoppers search websites better

Once shoppers land on a site, it’s up to the content, attributes and tags of products to guide the browsing experience, make a connection and transition to a purchase.  

In 2005, psychologist Barry Schwartz presented a Ted talk based on his book ‘The Paradox of Choice.’ In summary, Barry explains what happens when product/service providers offer a multitude of options to citizens, it can be counterintuitive and result in fewer sales.  

Going back to the long-tail keywords, attributes and tags set for products should reflect those words.  Fashion terms typically stay the same over time, however variations occur as trends emerge. Streamlining attributes and tags (create a glossary of common clothing terms) ensures consistency across an online store and bundles similar products together.  Providing a more personal product recommendation rather than endless scrolling of party dresses. Lucy doesn’t have time to look at everything, nor do many others.

It’s still relevant today that citizens are feeling stuck by the paradox of choice.  The indecision to make purchases, mixed with a fear of missing out then maybe a sense of buyers remorse.  

As a fashion retailer, rather than focus entirely on how to get more sales, switching the mindset from selling to building trust won’t take away from the business.  

Rather, and more importantly for the longevity of the business, it will create loyalty and advocacy.  For Lucy means feeling a whole lot more confident that’s who she wants to shop from again, and again.

No 4.  Focus more on organic growth over paid

Organic growth takes time and an invested effort to achieve, but it’s worth it.  

Thomas A. Edison once said “Opportunity is missed by most people because it is dressed in overalls and looks like work.”

When marketing tasks are implemented for a transactional return, such as paid advertising, the underlying message could actually communicate “this ad has been deliberately placed here because we want you to buy this thing you saw 5 sites ago,” and this is on repeat.  Whether it’s relevant or not, a company is willing to pay a lot of money to communicate a disingenuous message, thousands of times.

In 24 hours, Lucy found and purchased a gorgeous one shoulder party dress from a popular fashion site because it was the most relevant search result to match her query and offered a great selection of similar products. She also loved the shopping experience because of the extra content that appealed to her.  These were in the form of interesting blog posts, on-trend social channels and attention-grabbing conversational emails. All the activities and touch points, when executed with value in mind, work harmoniously together to create a memorable shopping experience.

The goal is to strike a balance, use paid advertising with empathy and follow through with great content, relevant descriptions, an optimised site and awesome social channels to turn a customer into a shopping bestie.  

The Okkular team have developed product attribute tools especially for fashion ecommerce businesses. By automating the tag-generation process, it helps small and medium sized businesses increase discoverability with potential shoppers and accelerate business growth organically.