After 7 years of consulting and doing CRO for eCommerce stores, my company just signed it's 1st equity deal with a hot new jewellery brand killing it on TikTok.
These guys are grassroots at the moment and only doing about $15K per month in sales. But here are some reasons why we started working with them:
1) High margin product
2) Low shipping costs
3) Strong social media presence
4) 40% repeat purchasers
5) Founder is hardworking, knows their product/market, and we have good vibes together
Other than that, it's a tear down. The site is basic and converts at below 0.5%. Ads channels are not profitable. Email marketing is basic/none existent on many levels.
For those asking why I didn't just start the company myself and own 100% my answer is simple. I'm good at data, marketing, and conversion optimization. All the product stuff – sourcing, product design, customer service, inventory management, social media – are not my skill set.
But I'm still curious, did I miss anything? What else should I consider before making this move to partner with eComm founder?
You’re missing out on ecommerce sales—the data shows it. Almost 70% of people adding items to their online shopping cart will exit without buying. Here’s the data behind why people abandon their carts (and what you can do to fix it).
Note: the links have been removed to comply with the rules. I have put them down in the comments.
I have selected the most popular web scraping tools that are friendly for people with little programming skills. Don't be fooled by their simplicity, some of them also support advanced programmable functions.
I have ordered them according to my personal preference (favorites at the end). Of course, this is an opinion and I recommend you do your own research.
Import.io: has gained popularity for the way it automatically converts any website into structured data and for its nice interface. Although it can be useful with simple web structures, it is not very good for various types of websites.
Dexi.io: similar in usability to Parsehub. Requires more advanced programming skills compared to the following scrapers. Has three types of robots available: extractor, crawler, pipes.
Parsehub: it can deal with complicated scenarios. Although it is intended to offer an easy web scraping experience, a typical user will still need to be a bit technical to fully understand many of its advanced functionalities.
Mozenda: it is one of the "oldest" web scraping software on the market. It has an attractive user interface, and very powerful and advanced options. There is not much to criticize it, except….. It's very expensive… and there's no free version 🙁
Octoparse: this is my favorite. Like Mozenda it is very simple to use and has powerful advanced options. It guesses the fields surprisingly well, so it saves a lot of time.
Data, analytics and business intelligence are common topics in the business world. Businesses across sectors, including ecommerce, are investing heavily in new technologies around data collecting and use of data.
That’s because data-driven decision making is more important than ever for ecommerce businesses as they seek to understand their audience, make tactical business decisions, and stay ahead of competitors.
However, while most businesses are well aware of the importance of leveraging data for the business insights it can provide, many struggle with best practices around using data to inform business outcomes.
In this post, we’re sharing some of the challenges ecommerce businesses face with data, how the right combination of strategies and technology solutions can help provide much-needed insights, and examples of ways BigCommerce merchants are using data solutions and insights to drive their business forward.
The Challenge: Too Much Data, Not Enough Insights
According to a report by Forrester called “Data Literacy Matters,” 90% of global data and analytics decision makers are focusing on prioritizing data insights in business decision making. The same report indicates that 91% of organizations report that they struggle with improving their use of data for business insights.
Businesses are more eager than ever to make investments in data and recognize its importance. Yet, many still struggle to turn their data into insights — and these insights into actions.
In fact, a Forrester states that between 60% and 73% of all data within corporations goes unused. Additionally, data from Statista identifies that 25% of companies are struggling with too much data.
This is where technology solutions can help you build a data-driven business.
Technology Solutions That Can Help You Make Data-Driven Decisions
Utilizing the right combination of data solutions is one way merchants can generate insights that allow them to make data-driven decisions and create customer experiences that help their businesses grow.
1. Data warehouses.
A data warehouse is a central repository or data catalog of integrated data, usually from multiple sources. A strong data warehousing architecture can provide a business with valuable data points.
It isn’t just huge enterprises that can use data warehouses to gather information that is relevant to their businesses. Data warehouse tools can work with businesses of all sizes. While the term “warehouse” brings to mind a physical place, many tools are available on the cloud, making them ideal to scale to the size you need.
Google BigQuery works in conjunction with Google Cloud Storage. It’s a fully managed data warehouse on RESTful web service that offers a scalable and cost-effective place to store your data. They also have a generous freemium tier and an easy-to-use UI which makes the tool accessible to a broader group of users.
2. Business intelligence solutions.
Data warehousing is a part of business intelligence. So what’s the difference between a data warehouse and a business intelligence solution? Essentially, data warehouses are tools that help you store the data while business intelligence solutions help you to analyze the data in concrete ways to support data-driven decision making and forecasting.
These tools can help you take the abundance of data you have and view it in dashboards that make sense to your various teams. Here are a few examples of these tools:
Google Data Studio is a data visualization tool that provides your team with some powerful ways of looking at your data. It has the advantage of being free and tightly integrated with Google BigQuery. Additionally, BigCommerce merchants can take advantage of pre-built reports to get started with Google Data Studio.
Tableau describes itself as a data visualization software with the goal of helping anyone to understand their data.
Microsoft Power BI is an industry leader in the business intelligence solutions field. Run by Microsoft, the solution provides interactive data visualizations with easy-to-understand dashboards.
3. Customer data platforms.
Today’s customers seldom just visit one store, make a purchase, and go about their life. They research and shop across multiple sites and platforms before making a decision. Tracking that omnichannel customer journey is where customer data platforms come in.
Customer data platforms, or CDPs, collect data to build customer profiles that can help inform marketing efforts. They work by capturing information as customers move across each touchpoint and aggregate the data so that it can be used by other business intelligence systems.
CDPs can help your business avoid data silos by making sure your teams know who your customers are, how they shop, and what makes them tick. The better you know your customers and their needs, the better you can market to them and solve their issues.
Segment is an example of a CDP that integrates with other business intelligence tools, as well as the BigCommerce platform, and allows you to unify your view of your customers across all products and channels.
Personalization solutions enable businesses to transition from a one-to-many customer marketing strategy to a one-to-one approach. With personalization solutions, you can deliver custom experiences for each shopper through dynamic content, product recommendations, discounts and offers and so much more. Here are some examples of personalization solutions in the BigCommerce partner ecosystem:
Understanding how your customers behave online can give you powerful insights into what’s working and what’s not on your ecommerce site. At its most basic, analytics refers to systematic computational analysis of data, which can be used to measure metrics across web, marketing, search and sales.
Here are some examples of analytics solutions in the BigCommerce partner ecosystem:
BigCommerce Provides an Open Platform for Data
The above types of data solutions have something in common: they rely on each other to work. Business intelligence isn’t something accomplished by one tool, but by a system working together to gather, store, and analyze data into actionable insights. Data-sharing between systems is an important part of this.
The key to taking advantage of the power of data is communication. That is to say: communication between data tools. There is no point in gathering and storing data if you can’t analyze it. And there’s no point in having it analyzed if it’s not viewable in a way that is meaningful for your teams.
That’s why at BigCommerce, we embrace a philosophy of openness, so that you have control over your data and can use the solutions that will have the biggest impact on your business — we like to call this our Big Open Data Solutions.
Big Open Data Solutions is a full product suite featuring both native and best-of-breed partner data solutions that give merchants the ability to aggregate, analyze, understand and use online store data to gain insight into customer behavior to enhance decision-making and improve business performance.
How BigCommerce Customers are Making Data-Driven Decisions
Here are some examples of how BigCommerce merchants are leveraging our Big Open Data Solutions to generate insights and make decisions.
Origin, an apparel and nutrition brand that handcrafts its products in the mountains of Maine, has been optimizing their tech stack to keep up with channel growth. Specifically, the company has leveraged the BigQuery integration and pre-built Data Studio reports to harmonize consumer data from multiple sources as part of their overarching omnichannel strategy.
“BigCommerce’s BigQuery integration allowed us to provide clean, actionable data while avoiding (error prone) manual reporting in order to make better decisions for the business. It’s been key in unifying our data and providing the insights required to make the right investments,” Sid Martin, Systems Analyst at Origin.
For Garrett Wade, a premier provider of fine woodworking tools and hand tools for the garden, the BigCommerce integration with BigQuery has been “game changing” for the company’s analysts.
This integration with BigQuery allowed the business to start looking at actual, accurate data from day one. The company reported spending very little time cleaning and normalizing the data. Plus, they were able to utilize the data to verify the accuracy of the testing environment prior to our launch. This also allowed the company to develop vetted reports right away; thus, creating the space that the development team truly needs to do the more difficult report work.
Being able to analyze how shoppers perform and behave, then churn out detailed reports in Tableau from a single location is not only efficient for the company’s two-person development team, but cost effective.
“When we were evaluating the move to BigCommerce as our platform provider, the integration with Google BigQuery was not high on the decision tree, but after using it for several months now, I can honestly say that this feature confirmed that we made the right choice with BigCommerce. I highly recommend,” stated John Chan, Inventory Planning and Business Intelligence Analyst, Garrett Wade Company.
Fore Ladies Golf
Fore Ladies Golf, a woman-owned business committed to providing women golfers with high-quality golf clothes, launched successfully on BigCommerce in 2018. However, owner Jessica Benzing quickly realized that she needed a solution for reporting and analytics to build a more data-driven strategy for her business.
Turning to Glew, Jessica was able to get a handle on what was working, what wasn’t, and what she needed to do to continue to scale. With Glew, she has a view of her top KPIs to analyze Facebook and Google Ads campaigns; a report on inventory to help manage budgeting and ensure consistent stock levels; and customer segmentation data to run targeted campaigns to her VIP customers, discount shoppers and more.
We know that data has power. As consumers demand more personalized experiences from ecommerce, shop in more omnichannel ways, and generally turn to ecommerce more and more for their purchases, the need to collect and understand data is only growing.
Having an ecommerce platform that supports your data-driven strategy is going to be crucial. At BigCommerce, we believe open SaaS is the future — and data is an important part of that. Being able to choose the data solutions from warehousing to analytics that best support your business intelligence goals and having them able to easily communicate with each other will make all the difference in honing a streamlined data strategy.
Basically the title. SFP should theoretically be cheaper since you’re only paying category referral fees and no storage costs, but Whitebox charges an extra 10% on top of SFP fees as well. And does Whitebox charge for shipping, or is that part of the 10%?
Hi all! My wife and I started a dog treat subscription box 3 months ago and have been gaining traction. Our conversion rate is about 1% according to Shopify, so I'd love to get it higher (no duh!)
We're a bit strapped for cash and are trying to maximize organic orders. I'd really appreciate anyone's feedback on the site design, messaging, or offer to see if there is low hanging fruit. We offer three purchase options: a-done-for you box, custom boxes, and one-off non-recurring purchases.