From books to makeup to ingredients to movies, subscription services are now available for almost anything. Customers love them because, for a nominal fee, they get something new every month. And businesses love them because they get to hold on to customers for longer and get paid every month.
Sneakers have gone from sports shoes to fashion accessories to prized collectibles that people spend lots of money on. Inspired by this, North American ‘sneakerhead’ and entrepreneur, Kamaj Silva, launched SneakerTub, the world’s first sneaker subscription service. With it, people could finally get a new shoe fix every month from top brands like Nike, Puma, and Saucony without breaking their bank account.
Impressed by the SneakerTub idea, the brand was invited to pitch on the hugely popular business reality TV show Dragon’s Den. Kamaj himself presented and had top investors bidding against each other to put money into his startup. This earned SneakerTub a ton of publicity, which quickly turned into strong organic growth.
To keep its early momentum going and give sales another boost, SneakerTub decided the time was right to start advertising online. Focused on North America and targeting a young audience, the company initially used Facebook Marketing because it placed ads on both Facebook and Instagram.
In North America, online advertising is highly competitive with many, many brands bidding for exposure. It’s especially fierce amongst subscription services who earn more per customer because they’re willing to place higher bids. SneakerTub, whose goal was to scale profitably, suddenly found itself in a war against soaring customer acquisition costs. It tried to use the ad platform’s intelligent targeting tools to make its campaigns more efficient but, because they’re primarily focused on repeat business and new customers, they did not deliver the right results.
Desperate for a solution, Kamaj discovers that the most successful online advertisers use artificial intelligence (AI) to optimize and scale their campaigns. He learns that with AI, the vast amounts of data from SneakerTub’s website, CRM and campaigns can be correlated and analysed for insights which not only reduce acquisition costs but also boost revenue growth.
Excited about AI, Kamaj initially found that most AI services for digital marketing were expensive, complicated and took a long time to deliver results. Persistent, he eventually came across one option he thought might be a good fit. Alavi is an online AI application that focuses on decoding and optimizing the entire customer journey. It’s been shown to improve returns in just 30 days. Best of all, it’s developed specifically for small and medium businesses, which means it’s simple enough for even an inexperienced marketer to use and cheap enough for an up-and-comer like SneakerTub.
Connecting Alavi to SneakerTub’s website and ad platforms was seamless and its AI engine immediately kicked into gear. Analysing over 200+ variables, it reverse engineered the path customers to took to convert and found which personas had the highest intent to buy (including the critical insight that many parents were subscribing to SneakerTub for their kids). Alavi then suggested different audience and product combinations to boost results at every level of the sales funnel.
In just three months, using Alavi’s recommendations reduced SneakerTub’s customer acquisition costs, the company’s biggest headache, by 33%. They also increased return on ad spend by 118% and, best of all, rocketed revenue up by an incredible 212%! As Kamaj would later say “Alavi’s targeting was so precise and so powerful. It put the kick back in my kicks!”
Starting life as a small nursery in 1965, Far East Flora Holdings is today, one of Southeast Asia’s leading florists. While the company has established a network of brick and mortar stores in Singapore, Hong Kong and Malaysia, it was quick to recognise the potential of the internet as a retail channel and launched FarEastFlora.com (FEF) as early as 2000. Today, the e-commerce site, led by its Managing Director, Ryan Chioh, offers over 1,000 flower and gift options and delivers to more than 140 countries.
In recent years, to market its innovative products online, FEF has relied on pay-per-click (PPC) advertising through platforms like Google and Facebook. Though year-on-year traffic growth has been good, conversions and revenue have not met the company’s expectations. This recently became an especially serious issue because FEF was forced to raise its ad spends to counter increased competition as well as target broader audiences (who generally have a lower intent to buy) to grow its customer base. The company knew the situation was unsustainable and improvements had to be made.
What FEF urgently needed was to boost its return on ad spend so it could achieve profitable growth. MD Ryan firmly believed the key to this was data. While he knew his web analytics platform collected vast amounts of information on customers’ purchase journeys, he didn’t have a cost-effective way to analyse all of it. Overcoming this issue was imperative to identifying potentially profitable audiences and extracting insights that would make FEF’s digital marketing more competitive, effective and efficient.
The solution Ryan found was Alavi.ai (Alavi), an online application that uses artificial intelligence and data science to analyse marketing data. He was keen to give Alavi a go because of its proven record of helping small and medium businesses grow profitably by greatly improving their PPC advertising. Quick Setup. Quick Results.
For FEF’s Marketing Communications Manager, Chris Kok, linking Alavi to the company’s ad platforms and customer relationship management (CRM) data (which Alavi encrypted) was straightforward and took very little time. Once connected, Alavi’s automated AI engine quickly kicked into gear and identified products that were most likely to sell in the coming weeks, as well as cohorts to target for immediate returns and profitable growth. By providing a marketing workflow along with cohort attributes that were compatible with Google and Facebook, FEF was able to immediately launch campaigns on its preferred ad platforms.
In just 3 weeks, with Alavi’s AI, FEF improved its online marketing considerably. Return on ad spend (RoAS) was increased by 21.75%, while average order value (AOV) shot up by 20.33%.
When it comes to flowers and gifts, trends and tastes are constantly changing. To help FEF keep on top of what’s new, Alavi constantly tracks user behaviour, so the company has the insights it needs to keep innovating and keep marketing the right products to the right people. Alavi’s ability to perpetually identify new opportunities from the top to the bottom of the customer funnel will ensure FEF continues to accelerate its growth profitably well into the future.
As one of India’s first online luxury fashion retailers, Elitify.com is dedicated to giving fashion-forward shoppers the latest clothing and lifestyle products. With concierge-style services, an easy-to-navigate design and handpicked offerings from top international brands, Elitify delivers a highly personalized shopping experience. This is what sets it apart from standard e-commerce sites.
As a seasoned entrepreneur, Ritesh Srivastava, CEO of Elitify, understands better than most that in today’s uncertain and fast-changing business environment, data is the key to success, especially the ability to analyze it quickly. At Elitify, because of its stylish content, visitors range from qualified shoppers buying chic jumpsuits and dress shirts, to aspirational browsers who hope to make a purchase in the future. For Ritesh, analyzing visitor data quickly meant the company could separate buyers from browsers and market the right products to the right audiences with customized content – something that is now an absolute must for e-commerce companies.
To find a way to do this, Ritesh along with his Head of Digital Strategy & Performance Marketing, Mohit Malik, looked for marketing technology that could deliver insights into who their qualified shoppers are, what they care about, and what inspires or motivates them to make a purchase. It was for these reasons (and several other useful features) that Elitify chose Alavi, an online artificial intelligence application that specializes in audience profiling, precision targeting and predictive analytics.
Since October 2019, Alavi has been at the heart of Elitify’s marketing strategy and the company is consistently learning more and more about its visitors. One example of this is that after connecting to Elitify’s analytics and ad platforms, Alavi found that qualified shoppers were also interested in travel, food and restaurants. Elitify was not targeting these profiles in its remarketing campaigns, but once it did, the company saw a significant increase in its return on investment.
Alavi has also been analyzing visitor data to provide product recommendations, which Elitify has used to personalize ads and optimize ad spends. With Alavi, qualified shoppers and aspirational browsers, based on their viewing history and past actions, only receive content and suggestions that are relevant to them. This not only increases engagement but has also been shown to boost conversions.
Determined to harness the power of data, Ritesh and Mohit’s efforts have clearly been vindicated. After just one month of using Alavi’s AI-powered product and audience insights and recommendations, the Elitify team has increased their return on ad spend (RoAS) by 45%, reduced cost per acquisition (CPA) by 24% and improved conversion rates by 40%. Stylish results for a very stylish business.
Macmerise is a rising star in India’s tech gadgets and accessories industry. It is best known as India’s first decal manufacturer and the first company in the country to be awarded licensing rights by major Hollywood studios including Disney, Marvel, Lucas Films and Warner Bros (DC Comics).
Like most online retailers, Macmerise invested significantly in pay-per-click (PPC) marketing to grow its business. While initial results were good, increased competition eventually resulted in soaring acquisition costs, diminishing returns and, worst of all, stagnant revenue growth.
To optimize its PPC marketing, Macmerise relied heavily on the targeting and conversion features offered by online ad platforms, like Facebook and Google These are tools every advertiser has access to, which meant Macmerise and its competitors were using similar strategies. Macmerise CEO, Sahil Shah realised that the company’s digital marketing did not have any competitive advantage.
To differentiate its strategies, Sahil and the company’s digital agency, Omnikon, searched for new marketing technologies. They wanted an application that would deliver a deeper understanding of how customers were engaging with their products and content and then identify new audiences that have a high probability of buying from Macmerise versus the competition. After an exhaustive search, they discovered Alavi.ai (Alavi), an online application whose artificial intelligence has helped brands across a broad range of industries greatly improve their digital marketing.
For Macmerise, setting up Alavi was simple and intuitive. In just a few of hours, Alavi was connected to all of the company’s ad platform analytics and automatically started searching for the company’s most profitable audiences. To do this, it used artificial intelligence to analyse the relationships between millions of data points. It then reverse engineered profitable conversion paths based on key metrics including cost per acquisition (CPA), return on ad spend (RoAS) and conversion rates.
Using Alavi’s cohort profiles and recommended workflows, Macmerise quickly launched a series of highly targeted campaigns via online platforms like Facebook and Google. The company also personalised each ad campaign’s creatives using the interests, affinities and demographic variables identified by Alavi.
In just four weeks, Alavi-powered campaigns beat all of Macmerise’s previous benchmarks. Cost per Acquisition reduced by 42%, Conversion Rates increased by 42% and Return on Ad Spend improved by 25%.
Buoyed by this success, up to 70% of Macmerise’s campaigns are now driven by Alavi, and the company is on track to doubling its revenue.
Established in 2002 with the aim of reviving South Asia’s rich textile heritage, the apparel retailer J. is today one of the region’s most successful brands. Catering to both women and men, the company operates over 100 local stores as well as another 20+ internationally in the UK, Australia, Canada, New Zealand, the UAE and Qatar.
With the internet revolutionizing shopping all over the world, J. launched its own e-commerce store. However, in recent years, with the number of brands selling online increasing almost exponentially, getting consistent growth has proved to be very difficult. This is because the competition on pay-per-click (PPC) advertising platforms (like Google and Facebook) has been especially fierce with marketing returns declining and budgets skyrocketing.
To fight rising marketing costs and reignite growth, J. knew it needed to optimize its PPC advertising and set itself two main goals: reduce cost per acquisition (CPA) for existing customers and acquire new ones with a controlled return on ad spend (RoAS).
To do this, it turned to data science, a tool that had helped many companies around the world solve similar problems. However, the cost of setting up its own data science team was prohibitively expensive. Fortunately, there were new marketing technologies that could help. After weighing the pros and cons of many of them, the company chose the advanced online targeting application, Alavi..
Offering both artificial intelligence (AI) and machine learning capabilities, Alavi was not only affordable but could quickly and easily integrate with the brand’s existing infrastructure and ad platforms. Upon connecting Alavi, its AI engine analysed a variety of variables from its marketing and customer data to identify audiences that were highly profitable and worth investing in. The insights Alavi provided helped the company target desirable cohorts with pinpoint accuracy and eliminate ones that had very little chance of converting. It also assisted the marketing team in developing ads that would improve engagement with the audiences it recommended so the company would get better returns.
Working with Alavi’s customer success team, the apparel brand launched a series of campaigns that were closely monitored to test the application’s effectiveness. In just 4 weeks, the Alavi.ai-assisted campaigns delivered results that not only exceeded expectations but broke existing standards: CPA was reduced by 77%, average order value grew by 50% and RoAS increased by 300%.
Buoyed by their success, J. is now gearing up to test Alavi.ai’s other advanced features, such as data-driven attribution modelling and engagement optimization. The battle for online success in the apparel industry requires strong allies, especially ones you know you can count on.
Launched by one of the biggest names in Pakistan textiles, Sapphire is a celebrated fashion brand known for exquisite designs at affordable prices. Built on an uncompromising commitment to quality, the company offers everything from clothes and shoes to bags and linen through its e-commerce site.
But with online shopping booming in Pakistan and barriers to entry relatively low, new companies are entering the fashion space all the time. There are already over 60 brands selling clothes online who get between 20,000 and several million site visits per month. Most of them are fighting to attract, engage, convert and retain the same audience segments.
This rapid increase in competition was a major challenge for Sapphire because it raised the company’s pay-per-click (PPC) marketing costs substantially on multiple ad platforms including Google and Facebook. Sapphire needed to find a solution that would help it both in the short term and the long term.
By studying what was happening internationally, Sapphire’s management team fully understood the potential of data science and how it could substantially improve online advertising returns as well as deliver consistent outcomes. After weighing the pros and cons of investing in their own data science team, they explored marketing technology options with similar capabilities.
One ‘martech’ that caught their eye was the precision targeting application, Alavi. It performed predictive analytics using customer user behaviour, which would allow Sapphire’s digital marketers to quickly and easily target their most profitable audiences. This would help maximise the efficiency and effectiveness of their campaigns. Also, because it was developed for small and medium businesses, Alavi was affordable and had the potential to deliver results almost immediately.
An online application, connecting Alavi to Sapphire’s web analytics and marketing platforms (Google, Facebook etc.) was simple and fast. Once linked, Alavi’s artificial intelligence (AI) and machine learning capabilities started working right away. Using data science to analyse data generated from past campaigns, Alavi was not only able to identify the best audiences for Sapphire’s current efforts but also audiences for expanding and remarketing.
In just one quarter, on the campaigns Sapphire used Alavi, digital marketing spends were finally optimized. This resulted in bigger earnings from existing customers as well as the acquisition of many new ones. Thanks to Alavi’s data science capabilities, Sapphire beat its return on ad spend (RoAS) target by as much as 35% and increased its average order value (AOV) by 16%.
Established in 1993, Image is a sophisticated and progressive fashion brand known for putting a modern twist on traditional styles. Operating in an intensely competitive industry, it has distinguished itself by consistently delivering products and experiences that are unique and captivating, such as curated collections based on innovative themes like ‘Monsoon’ and the ‘Garden of Versailles.’
While Image has its own branded ‘brick and mortar’ shops, the company has been very focused on its online store where it offers its entire catalogue to customers around the world. With a fast-growing range of products and collections to market, the company knew it needed to have a consistent and sustainable return on ad spend (RoAS) if it was to meet its ambitious growth targets.
When Marium Ahmed, Image’s Marketing and E-commerce Director, first met Zulfiqar Khan, head of SIAR Digital, the brand’s new e-commerce services agency, the issue of RoAS was discussed at length. They concluded that Image needed to be very dynamic and precise with its online audience targeting. This would allow the company to get more repeat business as well as expand its customer base while keeping ad spends in check.
Zulfiqar is a partner of Alavi, an online artificial intelligence (AI) application with a proven record of helping small and medium enterprises (SME) improve their audience selection and grow their revenue. He believed that by adding Alavi to Image’s marketing tech stack, the company would be able to get the results they wanted.
The onboarding process for Alavi was simple and SIAR Digital, with help from the application’s success team, started launching campaigns for Image using Alavi’s AI-powered insights. To capitalize on opportunities for repeat business at the bottom of the marketing funnel, Alavi’s ‘Retention’ function was used. While good digital marketers generally know who their loyal customers and big spenders are, the ‘Retain’ function helped Image and SIAR Digital take this a step further by identifying which of these individuals would probably make a purchase in the next 30 days. This information was then used to boost the brand’s remarketing campaigns.
As would be expected, some of Alavi’s automated data science capabilities took a bit of time to fully analyze and understand Image’s visitor and customer data. But once they did, the application’s ‘Optimize’, ‘Engage’ and ‘Expand’ functions kicked in and results were very impressive. For example, to attract new customers at the top of the marketing funnel, Alavi found several counter-intuitive insights, like people whose interests included ‘Looking for a Job’, which had a much higher chance of converting.
A unique feature of Alavi is that it didn’t just identify audiences interested in the type of products Image sold – it identified audiences who were interested in the Image brand. This allowed Image to run more efficient and effective campaigns for both regular and seasonal collections on Facebook and Google.
By providing productive insights and making it easy for Image and SIAR Digital to launch and optimize Image’s campaigns for new and repeat customers, Alavi has grown the brand’s conversion rates and online sales significantly. In just 3 months Image’s revenue from Facebook increased by 254% and its RoAS increased by 157%. With Alavi delivering new insights every week, Image will continue to build on its strong market position and get the consistent and sustainable returns it wants well into the future.
Meeta Gupta is passionate about designing safe and engaging toys. That is why the company she founded and heads, Shumee, only makes its toys with natural materials. They’re also designed to be ‘open-ended’, so a child has the freedom to decide how they want to play with them.
This commitment to offering sustainable alternatives to commercial toys is why Shumee is well on its way to changing the toy industry. The company already has a strong presence in India and in several major international markets, including North America, Europe, the Middle East and Southeast Asia.
But to continue its growth and achieve its ambitious goals, Shumee knew it needed to scale its direct-to-consumer efforts online. Though it was expanding at a steady rate, the company’s results on digital platforms like Facebook had plateaued due to increased competition as more and more brands advertised online and went after the same audiences.
Better targeting could definitely help overcome the problem of more competition. However, being a small and medium enterprise (SME), Shumee’s capabilities in this area were limited and relied mostly on trial and error as well as on built-in solutions from Facebook, such as ‘lookalike’ audiences. Unfortunately, these solutions tend to be imprecise and do not consider all the behavioral traits of a company’s existing customers. This meant Shumee was often targeting a much wider audiences than it needed to, and as a result, was not getting the profitable growth it wanted.
The company believed that to accelerate returns, it needed to better focus its online campaigns on individuals who specifically wanted to buy from its brand. This is why Meeta and Vivek, Shumee’s Head of Marketing, were interested in Alavi, an AI-powered marketing analytics application with a proven record of helping SMEs improve their online targeting.
To begin using Alavi, Vivek connected the online application to Shumee’s Google Analytics and Facebook Ad Manager accounts. This was followed by the encryption and uploading of the company’s customer transaction data. This entire process was done in a few quick steps and gave Alavi all the information it needed to start its advanced analytics.
The first Alavi feature the Shumee team used was the application’s ‘Retain’ function, which identifies a ‘Loyal Segment’ and a ‘Big Spender Segment’ – existing customers who are most likely to return and make considerable purchase in the next 30 days. Because of the actionable format in which Alavi provides this information, Vivek and his team were able to easily target these individuals through Facebook and significantly improve conversions and returns at both the middle and bottom of the marketing funnel.
Shumee also wanted to acquire new customers by growing and scaling its marketing top funnel. To do this, Vivek again used the ‘Big Spender Segment’ and created a lookalike audience on Facebook. He and his team then took advantage of Alavi’s ‘Expand’ function, which finds new audiences that can be used to further improve conversion rates and order values. For example, after analyzing over 200 variables in Google Analytics, Alavi suggested that Shumee target audiences interested in home gardening, TV, media and books. These were interest variables that the company had not targeted before but when they did, the new target audiences delivered strong returns.
After just one month of using Alavi, Shumee increased its return on ad spend (RoAS) by 65% and reduced its cost per acquisition (CPA) by 47%. And following these considerable improvements, the company increased its ad budgets for Alavi-led campaigns by 33%.
Thanks to Alavi’s predictive analytics, Shumee’s digital team was able to get new audience recommendations every week. They are especially happy about the amount of time they have been able to save just by using the application. Alavi eliminated the guess work and manual processes involved in deciding which new audiences to target and inputting them into ad platforms like Facebook.
Using Alavi’s insights and predictions, Shumee added greater precision to its targeting and was able to only go after individuals who are most likely to buy from its brand. Meeta, Vivek and the entire marketing team are seeing great organic growth and are continuing to make waves in the toy industry in India and around the world.