Original Source: https://ecommerce-platforms.com/articles/how-to-make-a-pricing-table-in-shopify

Having trouble making a pricing table in Shopify? A pricing table can simplify your customer’s decision making by comparing plans clearly. In this guide we will take you through each step on how to make a pricing table in Shopify, customise it and publish a pricing table.

Quick Summary

A Shopify Pricing Table builds trust and sales by comparing different pricing options, makes the buying process easier and faster.

Choose a pricing table app from the Shopify store, like POWR, Elfsight or Pricing Table – Pricing Plans to make an effective and beautiful table for your products.

Customise your pricing table with focus on clarity and aesthetics, use advanced settings and templates to showcase features and conversions.

What is a Shopify Pricing Table

A Shopify Pricing Table is a visual representation of different pricing options or packages for a product or service. It’s not just about listing prices, it’s about guiding the customer through their buying decision with clear comparative information. Showing different plans side by side allows the customer to see what they get for their money, makes the decision making process so much easier.

Transparency is key in eCommerce. When customers see transparent pricing information, it builds trust and integrity, makes them feel safe in their purchase decisions. This is especially true for Shopify pricing tables, which can increase sales and conversions by making options visible and understandable. In short a well designed pricing table can be a powerful tool that influences customer behaviour and drives more sales.

Also pricing tables help with sales by engaging the customer and reducing the time spent on the purchase decision. They clarify product offerings by showing options in an organised format, making comparisons easier. Pricing tables speed up the decision making and builds customer trust, boost your Shopify store’s performance.

Try Shopify

Set up Your Shopify Account

Before: Before you can make a pricing table you need to set up your Shopify account. It’s easy. Go to the Shopify website and click ‘Get Started’.

You will be asked to enter your email, password and store name. Once you’ve entered those details you will be taken to the Shopify admin panel where you can start setting up your store.

After:

Go to the Shopify website.

Click ‘Get Started’.

Enter your email, password and Shopify store name when prompted.

Once you’ve entered those details you will be taken to the Shopify admin panel.

Start setting up your store from the admin panel.

During the setup you will be asked questions about your business and will be required to share some personal information. This step is important as it will customise the Shopify experience for you. Once you’ve completed those steps you can log in with your registered email and password to access your account. Setting up your account correctly will make the process smoother when you start adding apps and building your online store.

You now have a well structured Shopify site and that’s the foundation for everything you will do next. From managing your stock keeping units (SKUs) to handling customer orders your Shopify admin panel will be your control centre. With your account set up you can now go to the Shopify app store and find the perfect pricing table app for you.

Choosing the Right Pricing Table App

Now that your Shopify account is set up it’s time to choose a pricing table app that fits your needs. There are many apps in the Shopify app store, each with different features and pricing. When choosing an app look for one that balances detail without clutter and has hover details for more information.

There are three options: POWR Product Pricing Table, Elfsight Product Pricing Table and Pricing Table – Pricing Plans. Each of these apps has its own strengths and can help you create a pricing table that will enhance your Shopify store’s layout and customer experience.

Let’s get into the details of each app.

POWR Product Pricing Table

The POWR Product Pricing Table is a powerful tool that allows you to add as many details as you want to your pricing tables, to your product presentations. One of its standout features is the ability to add a call-to-action (CTA) button directly to the tables which can increase conversions big time. This app is free, with a paid version starting at $5 per month for unlimited plans, custom CSS/JS and custom branding.

But the POWR Product Pricing Table has some limitations. Despite all the customization options it lacks author support from the support team which can be a problem for users who need technical help.

But for those who can figure out the features this app is a powerful way to create detailed pricing tables.

Elfsight Product Pricing Table

The Elfsight Product Pricing Table app has many customization options including the ability to change colours and fonts to match your brand. Users can choose between grid or column layout to display pricing information so it’s versatile for different presentation needs. The app also has highlights in table cells to draw attention to specific pricing options which can help with decision making.

Costing $6 per month Elfsight also has a free trial so you can try before you buy. The interface is user friendly so all store owners can create a pricing table even if you have no technical skills.

Zify Pricing Table

The Zify Pricing Table app is for showing products, services or plans side by side so users can compare easily. This app allows you to add pricing table and display pricing plans in a table format, create pricing tables, display related products for cross selling and highlight specific details in the table cells. Pricing table apps can also enhance user experience by having customizable options.

One of the best features of this app is the predefined skins so you can redesign your pricing tables without extensive coding knowledge. Overall it’s effective in increasing sales by presenting pricing options in a clear and organized way.

Further reading 📚

Shopify Pricing Plans and Fees (2024 Update!)

Shopify Review 2024 – Pros, Cons, and User Reviews

Install Your Chosen Pricing Table App

Now that you have chosen your pricing table app, the next step is to install it from the Shopify app store. Type ‘Pricing Table’ in the Shopify App Store search bar and press ENTER. Once you found the app, click the ‘Add app’ button to start the installation.

Once the app is added you will be taken to a new page where you can start creating your pricing table. Elfsight’s Product Pricing Table app has a free trial so you can try before you buy.

This initial setup is important to make sure everything is working before you start customizing your pricing table.

Create a Pricing Table

You have built your Shopify store, now you can create a pricing table using an EComposer template or start with a blank template. These templates are a base that you can customize to fit your needs.

You can modify product details after the initial setup so your pricing table reflects your products. Preview your pricing table before publishing to make sure everything looks and works as expected. This step will catch any errors and give your customers a smooth experience.

Customize Your Pricing Table

Customization is what makes your pricing table unique. You can change the layout structure of the pricing table and add video background from various sources to make it dynamic. You can also modify background colors, borders, fonts and individual column colors to match your brand.

Advanced settings allows you to control visual aspects like code, animation and background visibility so you can have a highly customized design. Using templates will make the process easier and you don’t need to have design skills to look professional.

Customization will make your pricing table look good and communicate your pricing options to your customers. To make it better you can add pricing tables for different customer needs.

Publish Your Pricing Table

Before you publish your pricing table make sure to review it for final tweaks. Test your pricing table for functionality and visual appeal to make sure it works across all devices.

Once you’re done with the design save your work in the editor and click publish to make it live on your Shopify store. Publishing your pricing table will make it visible to your potential customers and improve their shopping experience and potentially increase sales.

Mistakes to Avoid

Too much information in the pricing table will confuse the buyer. Make sure to differentiate your subscription plans so your customers won’t get frustrated. Consistent formatting and layout will help the user to understand and show excluded features from each plan to not mislead the customer.

And not highlighting the pricing details visually will make you miss sales. Make sure your pricing table is mobile responsive as many customers shop on tablets and smartphones. Avoid these mistakes and you will have a clear, concise and effective pricing table that will improve customer experience and sales.

Optimize Your Pricing Table for More Sales

A good pricing table can increase your average order value and overall revenue. By showing features and benefits you can increase your conversion rate. Adding subscription options and promotional pricing will show flexibility and will attract more customers.

You can also cross sell related products in the pricing table by recommending additional products to the customer. Show discounts through visual engagement like strikethrough pricing will show value and attract the buyer. Automatically offering discounts at checkout will make the process smoother and will increase conversion rate.

Flash sales and personalized discount offers will create urgency and will drive sales in a short period of time. Best practices is to test different layouts and offers to find the best combination. These will make your pricing table not only inform but also persuade the customer to buy.

Try Shopify

Conclusion

Making a pricing table in Shopify involves several steps from setting up your account to choosing the app to customizing and publishing the table. Each step is important to make your pricing table communicate your pricing options and improve customer experience.

Follow this guide and you’ll have a pricing table that will increase your sales and customer trust. Implement this and watch your Shopify store grow. Happy selling!

Frequently Asked Questions (FAQs)

How do I pick the best pricing table app for my Shopify store?

To pick the best pricing table app for your Shopify store evaluate your needs for customization, ease of use and features. POWR, Elfsight and Pricing Plans can do the trick!

Can I make a pricing table without coding skills?

Yes! Many pricing table apps especially on Shopify are user friendly and you can create and customize tables without any coding skills. Start now and make your pricing clear and beautiful!

How can I make my pricing table work?

To make your pricing table work focus on clarity and visual appeal and highlight the features and benefits. Remember, mobile responsive will improve user experience and conversions!

What to avoid when creating a pricing table?

To create a pricing table avoid overwhelming your audience with too much information, consistent formatting and differentiate your plans. By making it visually engaging and mobile friendly you will grab more attention and drive more conversions.

How to increase sales?

Cross sell, clear discounts and subscription options will increase your sales. Don’t forget to create urgency with flash sales and test different layouts.

The post How to Make a Pricing Table in Shopify: A Step by Step Guide appeared first on Ecommerce Platforms.

Original Source: https://ecommerce-platforms.com/articles/printify-vs-amazon-merch-on-demand

Printify vs Amazon Merch on Demand, which is the better option for print on demand sellers? Personally, after experimenting with both platforms myself, I’d say Printify wins hands-down. Amazon Merch on Demand makes it to set up your new business, and provides access to some excellent fulfillment services, but Printify gives you the power to scale.

With Printify, you can sell a wider range of high-quality customized products across a host of different channels (including Amazon). Plus, you get access to more advanced design tools, bonus services (like Printify Studio), and a free tool for launching your own pop-up store.

In my opinion, it’s a no-brainer, but if you want more guidance, read on for a full head-to-head comparison of Amazon Merch on Demand, and Printify.

Amazon Merch On Demand Vs Printify: The Quick Verdict

Printify is the better print on demand platform overall. I love that Amazon gives you the power to boost customer service with the delivery speeds of Amazon Prime, but Printify offers so many additional benefits. AI-powered design tools, a pop-up shop creator, and a wider product catalog are just some of the great things Printify has to offer.

Merch by Amazon Pros and Cons

Pros 👍
Cons 👎

Pros 👍

Instant access to customers through a world-leading online marketplace
Prime shipping for faster delivery speeds
Fantastic quality assurance standards
Easy setup and functionality for beginners
Fast payouts for royalties
Analytics and reports to help you track top-selling products

Cons 👎

Very limited product range
Not many integration options
Royalties make it hard to make a huge profit
Lots of competition on Amazon

Printify Pros and Cons

Pros 👍
Cons 👎

Pros 👍

Hundreds of unique products to customize
Easy integration with various sales channels, pod platforms, and online marketplaces like Amazon, eBay, and Etsy
Excellent pop-up store creator (available for free)
Huge range of global manufacturers
Great branding options
Impressive AI-powered design tools
Importance of selecting a reliable pod supplier for quality products, fast shipping, and good customization options

Cons 👎

Pricing, product quality and shipping times vary
Customer service can be a little slow

Printify vs Amazon Merch on Demand: Pricing, Fees, and Profit Margins

Want to launch your print on demand business with minimal upfront fees? Good news, both Amazon Merch on Demand and Printify allow you to get started for free. Both platforms also allow you to sell shirts with minimal upfront fees. The pod business model enables entrepreneurs to sell custom-designed products without managing inventory, as platforms like Printify and TeeSpring handle production, shipping, and customer service.

Selling t shirts on Amazon is a profitable and growing business opportunity. The vast market size and growth potential for online t-shirt sales make it an attractive option for entrepreneurs.

Amazon Merch on Demand Pricing

There’s absolutely no fee for selling on Amazon Merch, and there are no “premium” plans available. However, you also don’t exactly earn all of the profits from every sale.

Amazon pays its designers “royalties” from each sale, and they’re not exactly fantastic. For instance, selling a $15.99 t-shirt will earn you a royalty of about $1.93. You can’t set your own prices and manage your own profit margins, like you can with Printify, which means the selling price is determined by Amazon.

On the plus side, this does mean there aren’t any upfront costs to worry about at all. You don’t have to figure out the base price of a product, or how to manage shipping fees. You just list an item for sale and wait for the profits to roll in.

Printify Pricing

Printify also allows you to launch a POD store for free, but it follows a slightly different process. You don’t pay anything for a free Printify account, but when a customer places an order with your company, you pay for the base cost of the product from your chosen manufacturer (this can vary). You could also potentially pay for the shipping if you want to offer free delivery.

The good news is that you maintain full control over your profit margins. If a manufacturer charges $11.99 for a shirt, you can charge your customer any price you choose, including setting a regular price and a sales price. Printify’s core product prices are pretty affordable too – particularly compared to alternatives like Printful.

If your business starts to grow, you can upgrade to a premium plan with Printify for $24.99 per month (paid annually), which upgrades your 5 store limit to 10 stores, and gives you up to 20% discounts on all products. There’s also an enterprise plan, for high-volume sellers, with custom pricing, and extra discounts on products. Plus, you can pay for extra services from Printify, like web development support (Printify Studio).

Read more:

Printful vs Amazon Merch on Demand (2024): Quick Comparison

Merch by Amazon Review (2024): The Complete Guide

Redbubble vs Merch by Amazon 2024: Which is Best?

Printify vs Amazon Merch on Demand: Core Features of Print on Demand Platforms

So, both Printify and Amazon Merch on Demand give companies a low-cost way to start a business. But how do they stack up from a feature perspective?

Demand sites play a crucial role in this ecosystem by providing platforms that facilitate print-on-demand services, helping independent creators generate traffic and sales. Printify, for instance, offers a wide range of products, including wall art, which allows designers to cater to diverse customer preferences and artistic styles.

Product Variety and Quality of T Shirts

Let’s start with something essential to any creator investing in print on demand, product variety, and printing quality. Printify is the clear winner from a variety perspective. It gives companies more than 900 products to choose from, ranging from popular options like t-shirts, to more unique solutions like branded coffee.

Alternatively, Amazon only really supports a handful of basic products, such as t-shirts, tote bags, and sweaters. I couldn’t find anything particularly “unique” on the platform, which seriously limits your opportunity to scale your sales by building a robust product portfolio.

The good news is that Amazon does have a great reputation for maintaining product quality, as the company uses the latest equipment to print design, and follows strict quality assurance protocols. They also handle customer support for you, so if there are any issues with the quality of your designs, Amazon will deal with refunding or replacing the order.

Unfortunately, Amazon doesn’t offer any discounts on sample products, if you want to order and evaluate your products yourself. However, you (and your customers) do get free shipping if you spend more than $25 on the merch platform.

Printify also promises its manufacturers use cutting-edge printing machinery and adhere to high quality standards. However, there is some variation in what you can expect to get, since you’re working with such a wide range of manufacturers. Again, you also don’t get any discounts on sample orders, if you want to test the product quality yourself.

Design and Customization Options

Another area where Printify really stands out over Merch by Amazon, in my opinion, is in design and customization options. With Printify, there are tons of different ways to customize your products with unique images, patterns, all-over print, and even branded labels.

The design tools you get make it easy to create truly impressive products. There’s even an integrated generative AI tool that can create unique images for you based on basic prompts. I also love all the free assets you get on Printify to help you add extra components to your designs. Additionally, Printify’s network of global providers requires manual association with each product, while Gelato’s advanced routing algorithm selects the most suitable print provider based on delivery location, enhancing fulfillment efficiency.

Amazon’s design tools and customization options are extremely straightforward. You can really only upload a design, resize it, and position it in the right location on a product. There are no AI tools, and no real options to add your own branding.

Integrations and Sales Channels

Ultimately, the more channels you can sell through, the more likely you are to make a significant profit. Amazon does give you the opportunity to sell on one of the most popular ecommerce marketplaces worldwide. It also gives creators permission to sell their designs anywhere, but you won’t get any direct integrations that make connecting different channels easier.

Printify, on the other hand, is a lot more flexible. It doesn’t have it’s own marketplace, but it does allow you to create a “pop-up store”, for free, so you can sell your products instantly without having to manage and run your own ecommerce site.

Printify also directly integrates with some of the most popular ecommerce platforms, from Shopify to Wix, as well as marketplaces like Amazon and Etsy. You can even connect the platform to TikTok shop if you want to take advantage of social media selling. Additionally, Printify makes it easy to set up an online store, providing a custom retail space for your products without the complexities of managing a full ecommerce website.

On top of all that, you can access Printify’s custom API, to create automated workflows that connect all of your different apps and tools directly.

Printify vs Merch by Amazon: Customer Support

Finally, we come to customer support. I think Printify wins again in this area. Amazon Merch on Demand limits the number of contact channels for its vendors. Merch vendors can only contact the team directly through email, but Amazon is known for being extremely responsive.

There are also some basic self-help resources available online, but nothing close to Printify’s huge selection of blogs, videos, tutorials, guides, and FAQs. Printify also delivers rapid customer support through chat and email, and most of the manufacturers you’ll work with through the site are extremely responsive and helpful too.

You can also purchase additional services from Printify, like design support and assistance with transferring products. The good news is that both Printify and Amazon Merch on Demand are very straightforward platforms, so you shouldn’t need a lot of extra help. However, Printify does provide a better level of end-to-end support for beginners.

Printify vs Amazon Merch on Demand: The Verdict

So, which platform is best? In my opinion, the obvious answer is Printify. It’s the more robust and powerful platform, offering a wider range of product options, more customization for your items, stronger design tools, and endless sales channels to choose from.

Amazon Merch on Demand does give you access to a leading global marketplace (to help you attract customers), and fast shipping with Prime, but that’s about it. In every other area, it falls behind Printify, limiting your scalability and growth as an online seller.

The post Printify vs Amazon Merch on Demand: Which is Best for POD Sellers? appeared first on Ecommerce Platforms.

Original Source: https://www.hongkiat.com/blog/backup-restore-iphone/

Imagine losing all your valuable photos, essential contacts, and crucial documents in an instant. It’s a nightmare scenario that happens more often than you might think.

Your iPhone could get dropped, accidentally submerged in water, or become completely unresponsive. Our iPhones hold vast amounts of personal and professional data, making iPhone data loss a potentially devastating issue.

Thankfully, preventing data loss is simple; all you need to do is perform regular iPhone backups. In this guide, we’ll show you the best ways to back up iPhone data, ensuring your information is always safe and retrievable.

Note: If your primary concern is backing up iPhone photos and videos, check out our post on how to back up iPhone photos to your Mac.

Table of Content

Why Backup Your iPhone?
Methods to Backup iPhone Data

Using iCloud
Using iTunes/Finder
Using Third-Party Software

Step-by-Step Guide

Backup with iCloud
Backup with iTunes/Finder
Backup with Third-Party Software

Conclusion

Why Backup Your iPhone?

Key reasons to back up your iPhone regularly include:

Recover data if your device is lost or damaged.
Ensure a smooth transition to a new device.
Restore data after resolving major issues.
Protect against data corruption or malware attacks.

Methods to Backup iPhone Data

Using iCloud
Apple’s cloud-based service for wireless backups, accessible from anywhere with internet.

Using iTunes/Finder
Local backup option using iTunes (Windows/older macOS) or Finder (macOS Catalina and later).

Using Third-Party Software
Applications offering flexibility and additional features for iPhone backups.

Backup with iCloud

Ensure your iPhone is connected to a stable Wi-Fi network.
Go to the Settings app on your iPhone and tap on your name at the top of the settings menu.

Select iCloud from the list of services.

Scroll down and select iCloud Backup.

Turn on the iCloud Backup toggle, or tap “Back Up Now” to start the backup immediately.

Backup with iTunes/Finder

Use a USB cable to connect your iPhone to your computer.
Open iTunes if you’re using a PC or Finder on macOS Catalina and later.
In iTunes, click on the iPhone icon or select your iPhone from the sidebar in Finder.

iPhone icon in iTunes

iPhone in Finder, under Location

Under the “Backups” section, select “This Computer” to store the backup locally.
For added security, check “Encrypt iPhone Backup” and set a password (optional).
Start the backup process by clicking “Back Up Now.“

Back up iPhone via iTunes

Back up iPhone via Finder

Backup with Third-Party Software

First, select a reliable third-party backup software, such as Dr.Fone or iMazing. These apps are well-regarded for their efficiency and ease of use. Check out our previous review on Dr.Fone.

iMazing app interface

Next, download, install, and launch the chosen software on your computer. Ensure you follow the installation prompts to complete the setup process correctly.

After installing the software, use a USB cable to connect your iPhone to your computer. The software should automatically detect your device and prompt you with the next steps.

Follow the on-screen instructions provided by the software to back up your data. The process may vary slightly depending on the software you choose, but generally, it will guide you through the necessary steps to ensure your iPhone data is safely backed up.

Final Thoughts

Whichever method you choose – whether using Finder on macOS, iTunes on Windows, or backing up directly to iCloud from your phone – the key is to make sure you back up your iPhone regularly.

The post How to Properly Backup Your iPhone Data appeared first on Hongkiat.

Original Source: https://smashingmagazine.com/2024/08/integrating-image-to-text-and-text-to-speech-models-part2/

In Part 1 of this brief two-part series, we developed an application that turns images into audio descriptions using vision-language and text-to-speech models. We combined an image-to-text that analyses and understands images, generating description, with a text-to-speech model to create an audio description, helping people with sight challenges. We also discussed how to choose the right model to fit your needs.

Now, we are taking things a step further. Instead of just providing audio descriptions, we are building that can have interactive conversations about images or videos. This is known as Conversational AI — a technology that lets users talk to systems much like chatbots, virtual assistants, or agents.

While the first iteration of the app was great, the output still lacked some details. For example, if you upload an image of a dog, the description might be something like “a dog sitting on a rock in front of a pool,” and the app might produce something close but miss additional details such as the dog’s breed, the time of the day, or location.

The aim here is simply to build a more advanced version of the previously built app so that it not only describes images but also provides more in-depth information and engages users in meaningful conversations about them.

We’ll use LLaVA, a model that combines understanding images and conversational capabilities. After building our tool, we’ll explore multimodal models that can handle images, videos, text, audio, and more, all at once to give you even more options and easiness for your applications.

Visual Instruction Tuning and LLaVA

We are going to look at visual instruction tuning and the multimodal capabilities of LLaVA. We’ll first explore how visual instruction tuning can enhance the large language models to understand and follow instructions that include visual information. After that, we’ll dive into LLaVA, which brings its own set of tools for image and video processing.

Visual Instruction Tuning

Visual instruction tuning is a technique that helps large language models (LLMs) understand and follow instructions based on visual inputs. This approach connects language and vision, enabling AI systems to understand and respond to human instructions that involve both text and images. For example, Visual IT enables a model to describe an image or answer questions about a scene in a photograph. This fine-tuning method makes the model more capable of handling these complex interactions effectively.

There’s a new training approach called LLaVAR that has been developed, and you can think of it as a tool for handling tasks related to PDFs, invoices, and text-heavy images. It’s pretty exciting, but we won’t dive into that since it is outside the scope of the app we’re making.

Examples of Visual Instruction Tuning Datasets

To build good models, you need good data — rubbish in, rubbish out. So, here are two datasets that you might want to use to train or evaluate your multimodal models. Of course, you can always add your own datasets to the two I’m going to mention.

Vision-CAIR

Instruction datasets: English;
Multi-task: Datasets containing multiple tasks;
Mixed dataset: Contains both human and machine-generated data.

Vision-CAIR provides a high-quality, well-aligned image-text dataset created using conversations between two bots. This dataset was initially introduced in a paper titled “MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models,” and it provides more detailed image descriptions and can be used with predefined instruction templates for image-instruction-answer fine-tuning.

There are more multimodal datasets out there, but these two should help you get started if you want to fine-tune your model.

Let’s Take a Closer Look At LLaVA

LLaVA (which stands for Large Language and Vision Assistant) is a groundbreaking multimodal model developed by researchers from the University of Wisconsin, Microsoft Research, and Columbia University. The researchers aimed to create a powerful, open-source model that could compete with the best in the field, just like GPT-4, Claude 3, or Gemini, to name a few. For developers like you and me, its open nature is a huge benefit, allowing for easy fine-tuning and integration.

One of LLaVA’s standout features is its ability to understand and respond to complex visual information, even with unfamiliar images and instructions. This is exactly what we need for our tool, as it goes beyond simple image descriptions to engage in meaningful conversations about the content.

Architecture

LLaVA’s strength lies in its smart use of existing models. Instead of starting from scratch, the researchers used two key models:

CLIP VIT-L/14
This is an advanced version of the CLIP (Contrastive Language–Image Pre-training) model developed by OpenAI. CLIP learns visual concepts from natural language descriptions. It can handle any visual classification task by simply being given the names of the visual categories, similar to the “zero-shot” capabilities of GPT-2 and GPT-3.
Vicuna
This is an open-source chatbot trained by fine-tuning LLaMA on 70,000 user-shared conversations collected from ShareGPT. Training Vicuna-13B costs around $300, and it performs exceptionally well, even when compared to other models like Alpaca.

These components make LLaVA highly effective by combining state-of-the-art visual and language understanding capabilities into a single powerful model, perfectly suited for applications requiring both visual and conversational AI.

Training

LLaVA’s training process involves two important stages, which together enhance its ability to understand user instructions, interpret visual and language content, and provide accurate responses. Let’s detail what happens in these two stages:

Pre-training for Feature Alignment
LLaVA ensures that its visual and language features are aligned. The goal here is to update the projection matrix, which acts as a bridge between the CLIP visual encoder and the Vicuna language model. This is done using a subset of the CC3M dataset, allowing the model to map input images and text to the same space. This step ensures that the language model can effectively understand the context from both visual and textual inputs.
End-to-End Fine-Tuning
The entire model undergoes fine-tuning. While the visual encoder’s weights remain fixed, the projection layer and the language model are adjusted.

The second stage is tailored to specific application scenarios:

Instructions-Based Fine-Tuning
For general applications, the model is fine-tuned on a dataset designed for following instructions that involve both visual and textual inputs, making the model versatile for everyday tasks.
Scientific reasoning
For more specialized applications, particularly in science, the model is fine-tuned on data that requires complex reasoning, helping the model excel at answering detailed scientific questions.

Now that we’re keen on what LLaVA is and the role it plays in our applications, let’s turn our attention to the next component we need for our work, Whisper.

Using Whisper For Text-To-Speech

In this chapter, we’ll check out Whisper, a great model for turning text into speech. Whisper is accurate and easy to use, making it perfect for adding natural-sounding voice responses to our app. We’ve used Whisper in a different article, but here, we’re going to use a new version — large v3. This updated version of the model offers even better performance and speed.

Whisper large-v3

Whisper was developed by OpenAI, which is the same folks behind ChatGPT. Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. The original Whisper was trained on 680,000 hours of labeled data.

Now, what’s different with Whisper large-v3 compared to other models? In my experience, it comes down to the following:

Better inputs
Whisper large-v3 uses 128 Mel frequency bins instead of 80. Think of Mel frequency bins as a way to break down audio into manageable chunks for the model to process. More bins mean finer detail, which helps the model better understand the audio.
More training
This specific Whisper version was trained on 1 million hours of weakly labeled audio and 4 million hours of pseudo-labeled audio that was collected from Whisper large-v2. From there, the model was trained for 2.0 epochs over this mix.

Whisper models come in different sizes, from tiny to large. Here’s a table comparing the differences and similarities:

Size
Parameters
English-only
Multilingual

tiny
39 M
✅
✅

base
74 M
✅
✅

small
244 M
✅
✅

medium
769 M
✅
✅

large
1550 M
❌
✅

large-v2
1550 M
❌
✅

large-v3
1550 M
❌
✅

Integrating LLaVA With Our App

Alright, so we’re going with LLaVA for image inputs, and this time, we’re adding video inputs, too. This means the app can handle both images and videos, making it more versatile.

We’re also keeping the speech feature so you can hear the assistant’s replies, which makes the interaction even more engaging. How cool is that?

For this, we’ll use Whisper. We’ll stick with the Gradio framework for the app’s visual layout and user interface. You can, of course, always swap in other models or frameworks — the main goal is to get a working prototype.

Installing and Importing the Libraries

We will start by installing and importing all the required libraries. This includes the transformers libraries for loading the LLaVA and Whisper models, bitsandbytes for quantization, gtts, and moviepy to help in processing video files, including frame extraction.

#python
!pip install -q -U transformers==4.37.2
!pip install -q bitsandbytes==0.41.3 accelerate==0.25.0
!pip install -q git+https://github.com/openai/whisper.git
!pip install -q gradio
!pip install -q gTTS
!pip install -q moviepy

With these installed, we now need to import these libraries into our environment so we can use them. We’ll use colab for that:

#python
import torch
from transformers import BitsAndBytesConfig, pipeline
import whisper
import gradio as gr
from gtts import gTTS
from PIL import Image
import re
import os
import datetime
import locale
import numpy as np
import nltk
import moviepy.editor as mp

nltk.download(‘punkt’)
from nltk import sent_tokenize

# Set up locale
os.environ[“LANG”] = “en_US.UTF-8”
os.environ[“LC_ALL”] = “en_US.UTF-8”
locale.setlocale(locale.LC_ALL, ‘en_US.UTF-8’)

Configuring Quantization and Loading the Models

Now, let’s set up a 4-bit quantization to make the LLaVA model more efficient in terms of performance and memory usage.

#python

# Configuration for quantization
quantization_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_compute_dtype=torch.float16
)

# Load the image-to-text model
model_id = “llava-hf/llava-1.5-7b-hf”
pipe = pipeline(“image-to-text”,
model=model_id,
model_kwargs={“quantization_config”: quantization_config})

# Load the whisper model
DEVICE = “cuda” if torch.cuda.is_available() else “cpu”
model = whisper.load_model(“large-v3”, device=DEVICE)

In this code, we’ve configured the quantization to four bits, which reduces memory usage and improves performance. Then, we load the LLaVA model with these settings. Finally, we load the whisper model, selecting the device based on GPU availability for better performance.

Note: We’re using llava-v1.5-7b as the model. Please feel free to explore other versions of the model. For Whisper, we’re loading the “large” size, but you can also switch to another size like “medium” or “small” for your experiments.

To get our assistant up and running, we need to implement five essential functions:

Handling conversations,
Converting images to text,
Converting videos to text,
Transcribing audio,
Converting text to speech.

Once these are in place, we will create another function to tie all this together seamlessly. The following sections provide the code that defines each function.

Conversation History

We’ll start by setting up the conversation history and a function to log it:

#python

# Initialize conversation history
conversation_history = []

def writehistory(text):
“””Write history to a log file.”””
tstamp = datetime.datetime.now().strftime(“%Y%m%d_%H%M%S”)
logfile = f'{tstamp}_log.txt’
with open(logfile, ‘a’, encoding=’utf-8′) as f:
f.write(text + ‘n’)

Image to Text

Next, we’ll create a function to convert images to text using LLaVA and iterative prompts.

#python
def img2txt(input_text, input_image):
“””Convert image to text using iterative prompts.”””
try:
image = Image.open(input_image)

if isinstance(input_text, tuple):
input_text = input_text[0] # Take the first element if it’s a tuple

writehistory(f”Input text: {input_text}”)
prompt = “USER: <image>n” + input_text + “nASSISTANT:”
while True:
outputs = pipe(image, prompt=prompt, generate_kwargs={“max_new_tokens”: 200})

if outputs and outputs[0][“generated_text”]:
match = re.search(r’ASSISTANT:s*(.*)’, outputs[0][“generated_text”])
reply = match.group(1) if match else “No response found.”
conversation_history.append((“User”, input_text))
conversation_history.append((“Assistant”, reply))
prompt = “USER: ” + reply + “nASSISTANT:”
return reply # Only return the first response for now
else:
return “No response generated.”
except Exception as e:
return str(e)

Video to Text

We’ll now create a function to convert videos to text by extracting frames and analyzing them.

#python
def vid2txt(input_text, input_video):
“””Convert video to text by extracting frames and analyzing.”””
try:
video = mp.VideoFileClip(input_video)
frame = video.get_frame(1) # Get a frame from the video at the 1-second mark
image_path = “temp_frame.jpg”
mp.ImageClip(frame).save_frame(image_path)
return img2txt(input_text, image_path)
except Exception as e:
return str(e)

Audio Transcription

Let’s add a function to transcribe audio to text using Whisper.

#python
def transcribe(audio_path):
“””Transcribe audio to text using Whisper model.”””
if not audio_path:
return ”

audio = whisper.load_audio(audio_path)
audio = whisper.pad_or_trim(audio)
mel = whisper.log_mel_spectrogram(audio).to(model.device)
options = whisper.DecodingOptions()
result = whisper.decode(model, mel, options)
return result.text

Text to Speech

Lastly, we create a function to convert text responses into speech.

#python
def text_to_speech(text, file_path):
“””Convert text to speech and save to file.”””
language = ‘en’
audioobj = gTTS(text=text, lang=language, slow=False)
audioobj.save(file_path)
return file_path

With all the necessary functions in place, we can create the main function that ties everything together:

#python

def chatbot_interface(audio_path, image_path, video_path, user_message):
“””Process user inputs and generate chatbot response.”””
global conversation_history

# Handle audio input
if audio_path:
speech_to_text_output = transcribe(audio_path)
else:
speech_to_text_output = “”

# Determine the input message
input_message = user_message if user_message else speech_to_text_output

# Ensure input_message is a string
if isinstance(input_message, tuple):
input_message = input_message[0]

# Handle image or video input
if image_path:
chatgpt_output = img2txt(input_message, image_path)
elif video_path:
chatgpt_output = vid2txt(input_message, video_path)
else:
chatgpt_output = “No image or video provided.”

# Add to conversation history
conversation_history.append((“User”, input_message))
conversation_history.append((“Assistant”, chatgpt_output))

# Generate audio response
processed_audio_path = text_to_speech(chatgpt_output, “Temp3.mp3”)

return conversation_history, processed_audio_path

Using Gradio For The Interface

The final piece for us is to create the layout and user interface for the app. Again, we’re using Gradio to build that out for quick prototyping purposes.

#python

# Define Gradio interface
iface = gr.Interface(
fn=chatbot_interface,
inputs=[
gr.Audio(type=”filepath”, label=”Record your message”),
gr.Image(type=”filepath”, label=”Upload an image”),
gr.Video(label=”Upload a video”),
gr.Textbox(lines=2, placeholder=”Type your message here…”, label=”User message (if no audio)”)
],
outputs=[
gr.Chatbot(label=”Conversation”),
gr.Audio(label=”Assistant’s Voice Reply”)
],
title=”Interactive Visual and Voice Assistant”,
description=”Upload an image or video, record or type your question, and get detailed responses.”
)

# Launch the Gradio app
iface.launch(debug=True)

Here, we want to let users record or upload their audio prompts, type their questions if they prefer, upload videos, and, of course, have a conversation block.

Here’s a preview of how the app will look and work:

Looking Beyond LLaVA

LLaVA is a great model, but there are even greater ones that don’t require a separate ASR model to build a similar app. These are called multimodal or “any-to-any” models. They are designed to process and integrate information from multiple modalities, such as text, images, audio, and video. Instead of just combining vision and text, these models can do it all: image-to-text, video-to-text, text-to-speech, speech-to-text, text-to-video, and image-to-audio, just to name a few. It makes everything simpler and less of a hassle.

Examples of Multimodal Models that Handle Images, Text, Audio, and More

Now that we know what multimodal models are, let’s check out some cool examples. You may want to integrate these into your next personal project.

CoDi

So, the first on our list is CoDi or Composable Diffusion. This model is pretty versatile, not sticking to any one type of input or output. It can take in text, images, audio, and video and turn them into different forms of media. Imagine it as a sort of AI that’s not tied down by specific tasks but can handle a mix of data types seamlessly.

CoDi was developed by researchers from the University of North Carolina and Microsoft Azure. It uses something called Composable Diffusion to sync different types of data, like aligning audio perfectly with the video, and it can generate outputs that weren’t even in the original training data, making it super flexible and innovative.

ImageBind

Now, let’s talk about ImageBind, a model from Meta. This model is like a multitasking genius, capable of binding together data from six different modalities all at once: images, video, audio, text, depth, and even thermal data.

Source: Meta AI. (Large preview)

ImageBind doesn’t need explicit supervision to understand how these data types relate. It’s great for creating systems that use multiple types of data to enhance our understanding or create immersive experiences. For example, it could combine 3D sensor data with IMU data to design virtual worlds or enhance memory searches across different media types.

Gato

Gato is another fascinating model. It’s built to be a generalist agent that can handle a wide range of tasks using the same network. Whether it’s playing games, chatting, captioning images, or controlling a robot arm, Gato can do it all.

The key thing about Gato is its ability to switch between different types of tasks and outputs using the same model.

GPT-4o

The next on our list is GPT-4o; GPT-4o is a groundbreaking multimodal large language model (MLLM) developed by OpenAI. It can handle any mix of text, audio, image, and video inputs and give you text, audio, and image outputs. It’s super quick, responding to audio inputs in just 232ms to 320ms, almost like a real conversation.

There’s a smaller version of the model called GPT-4o Mini. Small models are becoming a trend, and this one shows that even small models can perform really well. Check out this evaluation to see how the small model stacks up against other large models.

Conclusion

We covered a lot in this article, from setting up LLaVA for handling both images and videos to incorporating Whisper large-v3 for top-notch speech recognition. We also explored the versatility of multimodal models like CoDi or GPT-4o, showcasing their potential to handle various data types and tasks. These models can make your app more robust and capable of handling a range of inputs and outputs seamlessly.

Which model are you planning to use for your next app? Let me know in the comments!

Original Source: https://www.hongkiat.com/blog/successful-ecommerce-app-guide/

Want to create a successful eCommerce app that generates high conversion rates and satisfies your customers? Well, your search ends here. Take a look at this detailed article.

In this comprehensive guide, we will share valuable tips, tricks, and best practices to help you build an outstanding eCommerce app.

Get ready to elevate your eCommerce app to new heights with our ultimate guide.

Table of Content

Why Building an eCommerce App Is Important?
Understanding the Key Features of a Successful eCommerce App
Researching Your Target Audience and Competition
Choosing the Right Platform for Your eCommerce App
Designing a User-Friendly and Visually Appealing App Interface
Implementing Secure Payment Gateways and Data Protection Measures
Optimizing Your App for Search Engines and App Stores
Utilizing Push Notifications and In-App Messaging for Customer Engagement
Testing and Optimizing Your eCommerce App for Performance and Usability
Interesting Stats on the eCommerce Industry Worldwide
Conclusion

Why Building an eCommerce App Is Important?

Freepik

In today’s digital world, having a strong online presence is crucial for any eCommerce business. While a well-designed website is essential, a dedicated eCommerce app can significantly expand your reach, allowing access to a global customer base beyond local boundaries.

Building an eCommerce app offers numerous advantages that can greatly boost your sales, enhance customer engagement, and drive overall business growth.

Here are some of the core benefits of having an eCommerce app:

Increasing Preference for Mobile Shopping

With over 70% of online shopping now being conducted on mobile devices, the preference for mobile shopping continues to grow. This trend highlights the importance of optimizing eCommerce apps for mobile users to capture and retain this significant portion of the market.

Seamless and Personalized Shopping Experience

Customers today expect a seamless experience when browsing, searching, and purchasing products on the go. A dedicated eCommerce app provides a tailored user experience, allowing for easier navigation and a more personalized shopping journey, which can lead to higher customer satisfaction and retention.

Enhanced Features and Functionalities

Modern eCommerce apps are equipped with enhanced features such as push notifications, in-app messaging, and location-based services. These functionalities help engage customers in real-time, offer timely updates, and create a more interactive and dynamic shopping experience.

Improved Customer Engagement and Connectivity

Staying connected with customers is key to driving repeat business. Through an eCommerce app, businesses can promote new products and offers directly to their users, while also providing personalized recommendations based on their shopping habits. This increased connectivity helps build stronger relationships with customers.

Increased Engagement and Personalization

By leveraging personalized content and targeted marketing strategies, eCommerce apps can expand their customer base and achieve higher conversion rates. This level of personalization not only improves customer engagement but also contributes to the overall success and growth of the eCommerce business.

To streamline the app development process and deliver a high-quality user experience, consider using a Bootstrap Admin Template. These templates offer pre-designed components and a responsive layout, making it easier to build a professional and attractive eCommerce app that meets modern standards and customer expectations.

Understanding the Key Features of a Successful eCommerce App

freeCodeCamp

Building a successful eCommerce app requires a deep understanding of the key features and functionalities that customers expect. These features not only enhance the user experience but also contribute to the overall success and profitability of your app.

User-Friendly and Intuitive Interface

An eCommerce app must have easy navigation to allow users to move effortlessly through the app. Quick product search functionality is essential for helping users find what they’re looking for without frustration.

A seamless purchase process, combined with a clean and visually appealing design, enhances the overall user experience. Additionally, a well-organized product catalog and a straightforward checkout process contribute to a user-friendly interface, ensuring that customers can complete their purchases smoothly and efficiently.

A Robust Product Search and Filtering System

A robust product search and filtering system is critical for improving the shopping experience. This feature allows for easy product searches, enabling users to filter items by categories, brands, or specific attributes. Sorting results based on individual preferences further enhances usability, allowing for quick product discovery.

Moreover, a well-designed search and filtering system can reduce cart abandonment by helping users find exactly what they want with minimal effort.

Secure and Convenient Payment Options

Providing a variety of payment methods, including credit/debit cards, mobile wallets, and digital payment platforms, is essential for accommodating different customer preferences. Implementing robust security measures ensures the protection of customer data, which is crucial for maintaining trust.

Overall, offering secure and convenient payment options contributes to a safe and trustworthy shopping experience, encouraging customers to complete their purchases with confidence.

You can explore eCommerce examples for inspiration.

Researching Your Target Audience and Competition

Freepik

Before you start building your eCommerce app, it’s crucial to research your target audience and understand their needs, preferences, and pain points. This research will help you design an app that resonates with your customers and gives you a competitive edge in the market.

How to Do It?

Analyze Customer Base: Gather demographic (age, gender, location, income) and psychographic (interests, values, shopping behavior) data to create user personas.
Study Competition: Analyze key players’ eCommerce apps to identify successful features, shortcomings, and opportunities for differentiation.
Gather User Feedback: Conduct surveys, focus groups, or interviews to understand customer pain points, preferences, and expectations. Use these insights to inform app design and features.

Choosing the Right Platform for Your eCommerce App

Choosing the right platform for your eCommerce app is crucial for its success, influencing the development process, features, and user experience.

There are many eCommerce platforms out there that you can consider, such as:

Squarespace: Best Overall E-Commerce Platform
Square Online: Best for Omnichannel Selling
Ecwid: Best for Existing Sites
Shopify: Best for Dropshipping
Wix: Best Drag-and-Drop Editor
Weebly: Best Value
BigCommerce: Best for Boosting Sales
WooCommerce: Best for Versatility
Big Cartel: Best for Creatives

Parameters to Consider When Choosing the Best Platform for Your App:

Compatibility: Integrates with existing systems (CMS, inventory, payment gateways).
Scalability: Handles growth and allows adding features easily.
User-Friendliness: Offers an intuitive interface and robust development tools.
Ease of Use: User-friendly interface and intuitive design.
Customization: Flexibility in design and functionality.
Payment Options: Variety and security of payment gateways.
SEO Features: Tools to optimize for search engines.
Mobile Optimization: Responsive design for mobile devices.
Customer Support: Availability and quality of support services.
Cost: Pricing structure and overall affordability.
Security: Robust security measures and compliance standards.

Designing a User-Friendly and Visually Appealing App Interface

Blinkist

The design of your eCommerce app is a critical factor in its success. A well-designed, user-friendly interface can not only enhance the overall customer experience but also increase conversion rates and customer loyalty.

As shown in the image above, Blinkist has used brand colors to add appeal and convey brand value. Its sleek, minimalistic interface focuses on core features, with intuitive navigation that makes it easy for users to find what they need.

To achieve similar results:

Prioritize simplicity and ease of use: Ensure a clean, uncluttered layout with intuitive navigation, prominent search functionality, and a streamlined checkout process.
Maintain visual appeal: Use consistent branding, color schemes, typography, and imagery that resonate with your target audience. This builds trust and recognition. Utilize UI Kits to streamline your design process.
Use responsive design principles: Deliver a user-friendly experience across all devices and screen sizes, improving accessibility and overall user experience.

Implementing Secure Payment Gateways and Data Protection Measures

Ensuring the security and privacy of your customers’ personal and financial information is of utmost importance when building an eCommerce app. Customers expect a safe and trustworthy shopping experience, and any breach of their data can have severe consequences for your business.

Use a PCI-Compliant Gateway: Ensure end-to-end encryption, tokenization, and fraud detection.
Encrypt Data: Apply strong encryption for storage and transmission.
Implement Access Controls: Use role-based access and multi-factor authentication.
Update Security Protocols: Regularly apply security patches.
Perform Security Audits: Conduct vulnerability assessments and breach tests.
Communicate Privacy Policies: Clearly inform customers about data protection practices.
Maintain Transparency: Provide updates on security measures and incidents.

Optimizing Your App for Search Engines and App Stores

In the competitive world of eCommerce apps, being discoverable is vital for driving traffic and increasing your customer base. Optimizing your app for search engines and app stores can significantly improve its visibility and help you attract the right audience.

When it Comes to Search Engine Optimization (SEO)

Focus on optimizing your app’s metadata, including the title, description, and keywords.
Conduct thorough keyword research to identify the terms and phrases your target audience uses to search for products or services like yours.
Utilize these keywords strategically throughout your app’s metadata to improve its ranking in search engine results.

Additionally, consider creating a dedicated landing page for your eCommerce app, complete with engaging content, visuals, and calls to action. This landing page can be optimized for search engines to drive more traffic to your app, increasing downloads and conversion rates.

When it Comes to App Store Optimization (ASO)

Pay close attention to your app’s title, icon, screenshots, and reviews.
Use catchy titles and icons that accurately represent your brand and offerings.
Craft compelling app descriptions that highlight your app’s key features and benefits.
Encourage your customers to leave reviews, as these can significantly impact your app’s visibility and download rates.

Utilizing Push Notifications and In-App Messaging for Customer Engagement

Keeping your customers engaged and informed is crucial for the success of your eCommerce app.

Push notifications and in-app messaging are powerful tools that can help you stay connected with your customers, promote new products and offers, and drive repeat business.

Push Notifications

Push notifications are a powerful tool to grab attention with timely updates about sales, new products, or personalized recommendations.

However, it is essential to strike a balance in frequency and content to avoid overwhelming customers, which can lead to app fatigue and reduced engagement.

In-App Messaging

In-app messaging allows you to deliver contextual, interactive content while customers are actively using your app.

This can include product recommendations, educational content, or feedback requests, all of which help to maintain engagement and ensure that your messages are well-received by users.

Personalize Notifications and Messages

Personalizing notifications and messages based on a user’s browsing and purchasing history, as well as their app usage patterns, can significantly enhance customer engagement.

By tailoring content to individual preferences and behaviors, you can boost conversion rates and create a more satisfying user experience.

Testing and Optimizing Your eCommerce App for Performance and Usability

Ensuring the performance and usability of your eCommerce app is crucial for providing a seamless customer experience. Regular testing and optimization should be integral to your app development and maintenance.

Conduct usability testing to identify pain points in your app’s user experience. This includes user testing sessions and collecting feedback through in-app surveys and reviews. Use these insights to improve your app’s design and functionality.

Monitor performance metrics such as load times, crash rates, and battery usage. Optimize code, use caching and compression, and optimize media assets to provide fast performance across all devices and network conditions.

Interesting Stats on the eCommerce Industry Worldwide
88% Consumers Hate Bad UX

Studies show that 88% of online consumers are less likely to return to a site after a bad user experience. This highlights the importance of delivering a seamless and enjoyable user experience to retain customers.

[Source: Sweor]

Up to 200% Better Conversion Rates

A seamless and intuitive interface can improve conversion rates by up to 200%. Investing in user-friendly design and functionality is key to maximizing sales and customer satisfaction.

[Source: Forrester Research]

94% of First Impressions Are Design-Related

Design is crucial to eCommerce success, with 94% of first impressions being design-related. A visually appealing website creates a positive initial impact on visitors.

[Source: ResearchGate]

86% Pay More for Better UX

Customer experience is directly tied to brand loyalty, with 86% of buyers willing to pay more for a better user experience. Focusing on customer satisfaction builds lasting relationships and drives repeat business.

[Source: Walker Information]

Over 5 Billion Global Internet Users

As of 2024, there are over five billion internet users globally, providing unparalleled opportunities for eCommerce businesses to connect with customers worldwide.

[Source: Internet World Stats]

3 Trillion USD in eCommerce Sales

Global retail eCommerce sales are projected to exceed 3 trillion U.S. dollars in 2024, highlighting the growing dominance of eCommerce in the retail sector.

[Source: Statista]

50.6% of Consumers Motivated by Free Shipping

Free shipping is the top motivator for online shopping, cited by 50.6% of consumers. Understanding consumer preferences like this helps reduce cart abandonment and increase sales.

[Source: SellersCommerce]

These statistics emphasize the critical importance of user experience, design, and customer loyalty in the success of eCommerce businesses globally.

Conclusion

Remember, the work doesn’t end once your eCommerce app is launched. Continuous monitoring, testing, and optimization are essential for maintaining a competitive edge and ensuring the ongoing success of your app.

Stay agile, adaptable, and responsive to your customers’ needs, and your eCommerce app will continue to be a valuable asset for your business.

Continuous testing and optimization are crucial as your app evolves. Regularly update your app based on customer feedback, industry trends, and new technologies to keep it relevant and engaging.

So, review the above points regularly. I hope you find this article helpful.

The post Things to Consider While Developing an eCommerce App in 2024 appeared first on Hongkiat.