New to the lingo? Here is an explanation of every e-commerce term you will ever need to keep up with the conversations in the business. 

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Understand the metrics, concepts and general lingo used by the top 1% within the e-commerce industry.

Ecommerce Glossary For The Next Generation

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Are you eager to know how you can get ahead of the competition and become more data-driven when it comes to running your e-commerce business more profitably?

A Data-Driven Attribution Model uses machine learning to assess each touchpoint's role in a customer's purchase journey. This provides a comprehensive understanding of marketing effectiveness and guides intelligent optimization of marketing spend in e-commerce.

A Data-Driven Attribution Model, in the context of e-commerce, is a sophisticated approach that leverages machine learning algorithms to determine the contribution of each touchpoint in a customer's purchase journey. Unlike rule-based models such as Last-Click or Time-Decay, this model considers all available data, including direct and indirect interactions, and statistically assigns credit to each touchpoint based on its impact on conversion. This model can provide a more accurate understanding of the effectiveness of different marketing channels and strategies, enabling e-commerce businesses to optimize their marketing spend and boost conversion rates intelligently.

A Data-Driven Attribution Model uses machine learning to assess each touchpoint's role in a customer's purchase journey.

What is data driven attribution?

Data-Driven Attribution Model

Affiliate marketing operates as a powerful strategy for drawing attention to products or services by leveraging the reach and influence of third-party affiliates. Essentially, it involves bringing potential customers who may not have been aware of a product or service to a business. This is achieved by targeting specific audiences through affiliates who use various techniques, including strong social proof, to encourage potential buyers to make a purchase.

One of the significant benefits of affiliate marketing is its ability to expand a business's reach beyond its immediate geographical area. By collaborating with affiliates who have established audiences in different regions or niche markets, businesses can tap into new customer segments that they might not have been able to access otherwise. Additionally, affiliate marketing minimizes financial risk for businesses. Since it operates on a commission-based model, businesses only pay affiliates when a sale is made, eliminating the need for upfront costs and reducing financial risk.

However, affiliate marketing is not without its challenges. It requires careful management and oversight to prevent fraud and abuse. Issues such as fake clicks, misleading promotions, or non-compliant practices can undermine the effectiveness of affiliate programs. Therefore, having some level of internal expertise is essential to monitor and manage affiliate activities effectively.


At Dema, we recognize the importance of effective affiliate marketing management. We offer comprehensive solutions for mapping and tracking affiliate performance, allowing businesses to monitor their affiliate programs closely and ensure optimal results. Our services include tools for tracking sales, analyzing performance metrics, and managing affiliate relationships, which help businesses maintain a successful and efficient affiliate marketing strategy.

A system where you reward partners (affiliates) for each visitor or customer brought about by the affiliate's marketing efforts.

Affiliate Marketing

An Attribution Model in e-commerce assigns credit for sales and conversions to different touchpoints in a customer's purchase journey, providing insights into channel effectiveness and aiding marketing optimization. E-commerce businesses need to understand the differences between attribution models, from simple ones like the Last-Click model to complex ones like the Time-Decay model or Data-Driven models, to allocate their marketing budget efficiently and increase conversion rates.

An Attribution Model in the context of e-commerce determines how credit for sales and conversions is assigned to different touchpoints in a customer's purchase journey. It offers insights into which channels (like social media, email marketing, or search engines) drive customer actions, helping businesses understand their marketing effectiveness and optimize their marketing strategies. These models can range from simple methods, like a Last-Click model that assigns all credit to the final interaction, to more complex ones, like a Time-Decay model that gives more credit to interactions closer to the conversion. Understanding the right attribution model is crucial for e-commerce businesses to allocate marketing spending efficiently and drive higher conversion rates.

An Attribution Model in e-commerce assigns credit for sales and conversions to different touchpoints in a customer's purchase journey, providing insights into channel effectiveness and aiding marketing optimization. 

Attribution Model

Average Order Value (AOV) measures the average amount customers spend per transaction at a store. It's calculated by dividing total revenue by the total number of orders.

Understanding AOV is crucial for segmenting customers based on their spending habits, which provides valuable insights into their purchasing behavior. This information helps in assessing the effectiveness of marketing efforts and pricing strategies, allowing you to optimize costs and enhance profitability.

To optimize AOV, consider these strategies across different stages of the sales funnel:

 Encourage customers to buy related products alongside their initial purchase.

 Offer upgrades or premium versions of the product they are already interested in.

 Provide incentives for future purchases to increase overall spend.

 Offer reduced prices for bulk purchases to boost transaction size.

 Create product bundles at a discounted rate to encourage larger purchases.

 Attract customers by removing shipping costs and offering easy returns, which can increase their willingness to spend more.

Dema can assist in optimizing AOV by providing live data and insights, enabling you to make informed decisions and adjust your strategies in real-time. Our tools help track and analyze customer spending patterns, so you can effectively implement these strategies to enhance your AOV and overall sales performance.

The average amount spent each time a customer places an order.

Average Order Value (AOV)

The break-even point is a critical financial metric where total revenue equals total costs, resulting in zero profit and zero loss. This point helps businesses determine the minimum sales required to cover all expenses, making it essential for evaluating pricing strategies, discount volumes, and overall product line performance.

Calculating the break-even point can be complex due to the need to account for various factors, such as fixed costs, variable costs, and discounts. Here’s a brief overview of these elements:

 These are costs that do not change regardless of the number of units sold, such as rent, salaries, and insurance.

 These costs fluctuate with the number of units produced or sold, such as raw materials and production labor.

 Reductions in selling price that can affect the revenue and consequently, the break-even point.

The traditional break-even calculation involves determining how many units need to be sold to cover both fixed and variable costs, considering any discounts offered. This requires a precise understanding of each cost component and their impact on overall profitability.

DEMA simplifies this process through its metric known as NGP3. NGP3 provides a unified view of the break-even point, integrating fixed costs, variable costs like fulfillment, returns and marketing into a single metric. Here’s how you can make use of this metric:

 By understanding the break-even point, you can assess whether your pricing strategies are effective. If the break-even point is too high, it may indicate that pricing adjustments or cost reductions are needed.

 With NGP3, you can evaluate how well different product lines are performing relative to their break-even points. This helps in identifying which products are profitable and which may require strategic changes.

 NGP3 consolidates multiple financial elements into a single metric, making it easier to perform break-even analysis without getting bogged down by complex calculations.

By leveraging DEMA's NGP3 metric, you gain clear, actionable insights into your financial performance, allowing you to make informed decisions about pricing, discounting, and overall product management. This simplified approach to break-even analysis helps you maintain profitability and optimize your business strategies more effectively.

The Break-Even Point, is when all revenue minus all costs, yield no profit or loss. It's crucial for businesses to track as it indicates the minimum sales required to cover costs and start earning profit.

Break-Even Point

A broken size curve in e-commerce happens when one or more of a product's variant(s) is out of stock, often reducing the conversion rate.

A broken size curve occurs when a retailer or e-commerce company runs out of one of the sizes or variants of a product. Typically, the most popular size goes out of stock first, decreasing the conversion rate. Unfortunately, merchants often overlook this issue and continue marketing the product as a best-seller, even though it is no longer available in that particular variant.

Fortunately, Dema offers a seamless solution for handling broken-size curves. With Dema, you can always stay informed about which products to market, where, and when. This way, you can optimize your marketing strategies and ensure maximum efficiency.

Broken Size Curve

Cart abandonment rate refers to the percentage of online shoppers who add products to their shopping carts but ultimately do not complete the purchase. 

Why should you care about Cart Abandonment?

This metric is a critical indicator of the effectiveness of an e-commerce site's checkout process and customer engagement strategies. On average, the cart abandonment rate exceeds 70%, making it a significant factor contributing to lost revenue for online retailers. This high abandonment rate highlights a crucial area for improvement in the online shopping experience.

What factors contribute to Cart Abandonment?

Several factors commonly contribute to cart abandonment. One of the primary reasons is high shipping costs. When customers reach the checkout stage and see unexpected shipping fees, they may reconsider their purchase, leading to cart abandonment. 

Another significant factor is the lack of diverse payment options. Shoppers are more likely to abandon their carts if their preferred payment method is not available. 

Additionally, a complicated or confusing user interface (UI) during the checkout process can drive potential buyers away. If customers find the checkout process cumbersome, lengthy, or difficult to navigate, they may opt to leave their carts behind rather than complete the transaction. 

How can you decrease your Cart Abandonment?

1. Many retailers offer free shipping thresholds or promotions to encourage completion of the purchase.

2. Offering a range of payment options, including credit cards, digital wallets, and buy-now-pay-later services, can help reduce abandonment rates.

3. Streamlining the checkout process, reducing the number of steps, and improving overall usability can significantly enhance the shopping experience and decrease abandonment rates.

Addressing these issues effectively requires ongoing analysis and optimization of the online shopping experience to ensure that customers find it convenient, transparent, and user-friendly.

The percentage of online shoppers who add items to their cart but leave without completing the purchase due to a change in mind, usually because of high hidden costs like shipping fee.

Cart Abandonment Rate

The churn rate is the percentage of customers who cease using your online store within a specific time frame, typically measured over a month.

Churn rate is crucial for assessing how well a business retains its existing customer base and its effectiveness in encouraging repeat purchases. A high churn rate can signal issues with customer satisfaction or engagement, while a low churn rate indicates strong customer loyalty and retention.

To gain a comprehensive understanding of a business’s growth, it is useful to analyze churn rate alongside the growth rate. This combined approach helps identify the net change in the customer base, providing insight into whether the business is expanding or losing ground. For example, if a business is gaining new customers rapidly but also experiencing a high churn rate, the overall growth may be limited or even negative.

For traditional e-commerce companies, accurately calculating churn rate involves several steps. First, gather data on repeat customers, focusing on their purchase history and the average time between transactions. Segment this data into meaningful periods, such as monthly or quarterly, to better understand purchasing patterns. This segmentation helps in identifying trends and anomalies in customer behavior.

Seasonality is another important factor to consider when calculating churn rate. Purchasing patterns can vary significantly throughout the year due to holidays, seasonal promotions, or other external factors. By accounting for these seasonal fluctuations, you can ensure that your churn rate calculations are more accurate and reflective of true customer behavior.


If you want to read more about churn rate and why churn rate matters read 

E-commerce retention explained: customer churn & why it matters

The percentage of customers who stop using your online store during a certain timeframe.

Churn Rate

Click-Through Rate (CTR) measures the proportion of users who move from one stage to the next in a marketing process, such as clicking on an ad after seeing it, or visiting an e-commerce site after opening a newsletter.

To accurately assess the effectiveness of your campaigns, you should compare CTR across different campaigns that have similar timeframes, ad copy, and target the same segment of the marketing funnel. This comparison helps determine whether a high CTR is translating into meaningful engagement and conversions.

While a high CTR can indicate that your content is capturing attention, it's essential to distinguish between high CTR and relevant CTR. A high CTR alone doesn't guarantee success if it leads to irrelevant clicks, which can waste ad spend and result in low conversions.

 Incorporate relevant keywords that resonate with your target audience.

 Create compelling CTAs that clearly guide users on what action to take next.

 Use eye-catching visuals to enhance appeal and engagement.

 Leverage hashtags to increase visibility and reach on social media platforms.

By implementing these strategies and analyzing CTR in context, you can better gauge the effectiveness of your marketing campaigns and make informed adjustments to improve performance.

CTR, or Click-Through Rate, measures the proportion of users who progress from one stage to another in a process, such as from seeing an ad to clicking on it, or opening a newsletter to visiting a linked e-commerce site.

Click-through-rate (CTR)

The Contribution Margin, a crucial profitability metric, is the leftover from Gross Sales after deducting all the direct costs of fulfilling the orders. Some argue that it is the same as Net Gross Profit 3, taking marketing spending into account. In contrast, others say marketing spending should not be part of calculating the contribution margin.

Contribution Margin in e-commerce is not the same to everybody. Why is that? It might be because people focus on different things in e-commerce, and when it comes to Contribution Margin, it's very clear that this is the case. So whenever Contribution Margin is mentioned as an important part of a discussion or a potential decision, you need to make sure that you all mean the same thing.

According to some people, Contribution Margin have different layers (1, 2, 3), and to other it is absolute and always means the same.

When someone is referring to "The Contribution Margin" it most often means the remaining amount from your Gross Sales after subtracting all the costs directly associated with selling a product. It is similar to Net Gross Profit 3, as both formulas calculate the difference between Gross Sales and the expenses tied to product sales. However, while Net Gross Profit 3 also includes marketing expenses, many calculate the Contribution Margin solely considering direct product costs.

Contribution Margin is an essential metric for determining a company's profitability and evaluating the cost-effectiveness of its products.

If you want to read more about Contribution Margin, and the different layers of it; 

click here to read our blog post about Contribution Margin

Contribution Margin

A customer’s journey through a sequence of steps aimed at achieving a desired action, typically a purchase, is known as the sales funnel. This funnel divides the conversion process from visitor to customer into distinct stages, allowing marketers to target and promote relevant ads based on where users are within the funnel.

Each stage of the funnel represents a different step in the customer journey, and it's common for users to drop out at various points. By analyzing these drop-off points and segmenting users, marketers can identify which parts of the funnel need attention and adjust their strategies to improve conversions. For example, if users are dropping off at the checkout stage, you might focus on optimizing the checkout process or offering incentives to encourage completion.

Customer preferences and behaviors can change over time, so it’s important to continually reassess and adapt the funnel to align with evolving needs. A robust marketing strategy should be flexible and responsive, addressing various segments of the funnel rather than focusing solely on one stage. This approach ensures sustained growth and relevance in a dynamic market.

Regularly updating and optimizing the funnel based on customer insights will help maintain engagement and drive long-term success.

A customer's journey through a sequence of steps designed to lead to a desired action, typically a purchase.

Conversion Funnel

Conversion rate measures the percentage of visitors who take a desired action on a website, such as making a purchase, signing up for a newsletter, or completing a form. For e-commerce sites, it specifically evaluates how effectively the conversion funnel performs and how smoothly users progress through the purchasing process.

Marketers typically track conversion rates regularly—weekly, monthly, quarterly, and yearly—to gauge the effectiveness of their strategies and identify areas for improvement. By monitoring these rates, businesses can better understand user behavior and optimize their sales funnels to enhance performance.

To improve conversion rates, consider implementing the following strategies:

 Strengthen your brand's identity to build trust and recognition with users.

 Use clear, compelling CTAs that guide users towards the desired action.

 Offer free shipping to reduce barriers to purchase.

 Incorporate reviews, testimonials, and user-generated content to build credibility.

 Allow users to make purchases without creating an account to streamline the process.

 Provide a variety of payment methods to cater to different preferences.

 Customize content and offers based on geographic location to better resonate with users.


At Dema, we leverage advanced machine learning models to enhance conversion rates. Our state-of-the-art technology analyzes data and optimizes strategies to ensure your marketing efforts are as effective as possible, helping you achieve higher conversion rates and improved business outcomes.

The percentage of visitors who take a desired action, generally making a purchase.

Conversion Rate (CR)

The cost of goods sold (COGS) signifies the total expense incurred in acquiring the products that a business sells. This figure represents the direct costs attributed to the production of goods or the purchase of inventory, appearing at the forefront of financial calculations when the products are sold. Essentially, COGS reflects the actual expense that a company pays to bring its products to market, encompassing not just the purchase price but also other related costs.

To accurately determine COGS, various methods can be employed, especially when products are purchased at different times and prices. One common method is the First-In, First-Out (FIFO) approach, where the cost of the earliest goods purchased is assigned to the cost of goods sold. Alternatively, the Last-In, First-Out (LIFO) method assigns the cost of the most recently acquired inventory to the cost of goods sold. Additionally, some businesses use a weighted average cost method to spread out the cost over all units sold.


Beyond the purchase price, COGS may also include ancillary expenses such as product handling, warehousing, and transportation costs associated with getting the products from suppliers to the warehouse. These additional expenses contribute to the total cost of bringing a product to market, impacting overall profitability.

Using advanced tools like Dema, businesses can input costs at a granular level to gain more precise insights into their profit margins. Dema allows for detailed cost analysis by country, category, collection, and size, enabling companies to fine-tune their pricing strategies and inventory management. Accurate determination of COGS is crucial for assessing business profitability and evaluating the efficiency of inventory management processes, especially when material costs are consistent. This metric helps businesses understand their gross margin and make informed decisions to enhance their financial performance.

The cost of goods sold signifies the total expense of purchasing the products sold, meaning the cost appears first when you sell the product.

Cost of Goods Sold (COGS)

Customer Acquisition Cost (CAC) is one of the most critical KPIs in e-commerce. It measures the total cost of acquiring a new customer. 

To track your CAC, you need to know your marketing spend and the number of new customers who have placed an order. CAC is not cost per order since that includes returning customers as well. Your profitability on new customers' first orders, in combination with a predicted lifetime value, will be the most important input variable in defining your maximum CAC.

Understanding and optimizing your CAC is crucial for driving profitable growth in your e-commerce business. However, in some cases, to boost brand awareness, CAC might be high temporarily but will lead to long term gains.

CAC can then be paired with LTV to understand if the business is targeting the right type of customers that will bring them profits. It is also crucial to note that CAC includes salary, agency fees,copy and design fees and payment processing fees.

All this is, of course, easy to monitor and analyze in real-time on the Dema platform so that you can make the best data informed decision that benefits your brand.

Customer Acquisition Cost (CAC) is one of the most critical KPIs in e-commerce. It measures the total cost of acquiring a new customer. To track your CAC, you need to know your marketing spend and the number of new customers who have placed an order. CAC is not cost per order since that includes returning customers as well. Understanding and optimizing your CAC is crucial for driving profitable growth in your e-commerce business. 



Customer Acquisition Cost (CAC)

Customer Lifetime Value (CLV) usually predicts the total value an e-commerce business can expect from a single customer account. It considers the revenue generated by the customer and compares it to the expected lifespan of the customer. This calculation helps businesses identify valuable customer segments that are most beneficial to the company.

When calculating CLV in e-commerce, it is typically based on gross sales instead of profit. This is because obtaining profit metrics for these calculations is often more challenging, while gross sales are typically always available.

A common method to calculate CLV based on gross sales is to use the formula CLV = (Average Purchase Value x Purchase Frequency) x Average Customer Lifespan.

Average Purchase Value is determined by dividing the total revenue over a set period by the number of purchases made.

Purchase Frequency is calculated by dividing the number of purchases made over a set period by the number of unique customers who made purchases during that period.

Average Customer Lifespan is the average number of years a customer continues purchasing from the e-commerce business.

By employing this formula, businesses often estimate the total gross revenue a customer will generate over their lifetime. This approach provides valuable insights into the potential value of customer relationships, extending beyond individual transactions or immediate profit. However, it is important to recognize that assuming all customers are identical often is misleading. Instead, a recommended approach for estimating newly acquired customers' value is utilizing an AI prediction model. This model enhances clarity by identifying which customers are more or less likely to yield significant value or become net negative customers for the e-commerce company in the worst-case scenario.

Dema offers an LTV Prediction Model, basing the customer's future value on actual profit and not just Gross Sales. You can read more about it here.

Customer Lifetime Value (CLV) is usually a prediction of the total value an e-commerce business can expect from a single customer account.

Customer Lifetime Value (CLV, LTV or CLTV)

Dropshipping is a fulfillment method where an e-commerce business does not maintain physical inventory of the products it sells. Instead, when a customer places an order, the e-commerce store purchases the product from a third party, who then ships the item directly to the customer.

This model allows businesses to operate with minimal overhead costs since there is no need to invest in inventory storage or manage stock levels.

With dropshipping, the e-commerce business focuses more on marketing and customer acquisition rather than on handling and storing products. This approach can significantly reduce the financial risks associated with holding inventory and can streamline operations, as the logistical aspects are managed by the third-party supplier. It also enables businesses to offer a wide range of products without the constraints of inventory management.


One of the most popular platforms for starting a dropshipping store is Shopify. Shopify provides a user-friendly interface and various tools designed to help entrepreneurs set up and manage their dropshipping businesses effectively. It integrates seamlessly with numerous dropshipping suppliers and offers a range of apps to enhance store functionality.

For businesses using Shopify, Dema offers integrations that simplify the process of importing store data for comprehensive profitability analytics. These integrations allow you to access detailed insights into your sales performance, track key metrics, and evaluate the financial health of your dropshipping operations. By leveraging Dema’s analytics, you can make data-driven decisions to optimize your marketing strategies, adjust pricing, and improve overall business efficiency. This enables you to focus on growing your business while ensuring that you have a clear understanding of your financial performance and operational success.

A fulfillment method in which an e-commerce business doesn’t keep the products it sells in stock. Instead, the e-commerce purchases the product after the customer has purchased the item from the e-commerce. The third party that the e-commerce buys the item from also ships it directly to the customer. This allows for low overhead costs and attention to fulfillment while putting more emphasis on paid marketing.



Dropshipping

Retention rate in e-commerce measures the percentage of customers who Retention rate in e-commerce is a crucial metric that measures the percentage of customers who continue to make purchases over a specific period of time.

Retention rate is essentially the inverse of churn rate, which measures the percentage of customers who stop making purchases over a given period. To calculate retention rate, you subtract the churned customers from the total number of customers and then divide by the total number of customers at the beginning of the period.

It reflects the ability of an e-commerce business to maintain its customer base and foster repeat purchases. Retention rate is particularly significant because acquiring new customers often involves higher costs compared to retaining existing ones. Therefore, a higher retention rate can lead to more sustainable and profitable growth.

Retention rate varies in importance depending on the e-commerce vertical. For example, subscription-based services or consumable products rely heavily on high retention rates to ensure ongoing revenue streams. Conversely, in industries where products are less frequently purchased, such as luxury goods, retention may be less critical but still valuable for maintaining brand loyalty and encouraging repeat business.

Why you should pay attention to Retention Rate

A small improvement in retention rate can have a substantial impact on a business due to compound effects. Retaining existing customers not only boosts immediate revenue but also enhances customer lifetime value (CLV). Over time, even minor increases in retention can lead to significant growth in overall sales and profitability. Loyal customers are more likely to make repeat purchases, refer others, and engage with your brand more deeply, contributing to long-term success.

Thus, focusing on strategies to improve retention—such as personalized marketing, excellent customer service, and loyalty programs—can be highly beneficial for enhancing overall business performance and achieving sustainable growth.

Retention rate in e-commerce measures the percentage of customers who continue to make purchases over a specific period of time. Depending on which e-commerce vertical you are in, your retention rate is more or less critical to assure sustainable and profitable growth since, typically, customer acquisition is more expensive than keeping existing customers. 



E-commerce Retention Rate

In the context of website analytics, an engaged session refers to a period during which a visitor actively interacts with a website. This engagement can take various forms, including clicking on links, scrolling through pages, filling out forms, or spending a certain amount of time on the site. The term implies that the visitor is not just passively browsing but is actively exploring and showing interest in the content or offerings of the website.

Why you should understand Engaged Sessions

Understanding engaged sessions is crucial because they indicate a higher level of visitor interest and interaction, which often correlates with the likelihood of conversion. Engaged sessions are a strong indicator that the content is resonating with the audience and that the website is effectively capturing their attention.

Why it can be tricky to track Engaged Sessions

Different ad platforms may define and measure engaged sessions in various ways, which can sometimes lead to inconsistencies and confusion. For instance, some platforms might track engagement based on specific actions like clicks or time spent, while others might use different criteria.

At DEMA, we offer client-side tracking that provides direct access to raw data related to engaged sessions. This approach reduces ambiguity and ensures more accurate data collection, allowing for a clearer understanding of visitor interactions. By analyzing engaged sessions, you can identify which marketing channels and content are driving the most meaningful interactions. This insight helps in optimizing your ad spend by focusing on the most effective strategies and channels, ultimately improving the return on investment (ROI) for your marketing efforts. Understanding which content and channels perform best allows you to allocate resources more efficiently and enhance the overall effectiveness of your digital marketing campaigns.

In the context of website analytics, an engaged session refers to a visitor's active interaction with a website for a given duration. This may include clicking on links, scrolling, or filling out forms. An engaged session usually implies that the visitor is actively interested in what your website has to offer and, therefore, exploring it.



Engaged Session

The process of receiving goods from suppliers, packaging the items, branding it, and then shipping orders to customers. Fulfillment also handles the returning part of the process from the customer back to the warehouse.

Order fulfillment encompasses the entire process of receiving goods from suppliers, preparing them for sale, and delivering them to customers. This intricate process begins with the receipt of products from suppliers, where items are inspected for quality and accuracy. Once verified, these products are then packaged, often with branded materials to enhance customer experience and brand recognition. The packaging stage ensures that products are protected during transit and presented attractively.

Following packaging, the items are shipped to customers, a step that involves selecting appropriate shipping methods and managing logistics to ensure timely delivery. Effective fulfillment operations not only involve shipping but also address the reverse logistics process—handling returns from customers back to the warehouse. This aspect is crucial for maintaining customer satisfaction and efficiently managing inventory. 

There are different types of fulfillment: inhouse, outsourced -the most popular option is amazon FBA and Hybrid. There are several types of fulfillment models businesses can adopt, each with its own set of advantages. Overall, the choice of fulfillment model can significantly influence a business’s operational efficiency and customer satisfaction.

Order fulfillment is crucial to the core of an ecommerce business as it reveals the efficiency of the business and impacts customer experience. Order fulfillment is central to the success of an e-commerce business as it directly impacts operational efficiency and customer experience. An optimized fulfillment process can enhance customer satisfaction by ensuring prompt and accurate deliveries, while also reducing operational costs.


Fulfillment

Gross Profit 1 is a company's profit after deducting the Cost of Goods Sold, which represents the costs associated with purchasing its products. This figure does not include fulfillment, marketing, or overhead costs such as rent, utilities, salaries, or returned items.

Gross Profit 1

Gross Profit 2 measures profitability after accounting for the costs and fulfillment costs associated with purchasing its products. Fulfillment costs include storage, order processing, packaging, and shipping expenses. Like Gross Profit 1, this figure does not consider the impacts of marketing or overhead costs such as rent, utilities, and salaries. Returned items are also not deducted in the calculation of Gross Profit 2.

Gross Profit 2

Gross Profit 3 encompasses the profitability measure that includes the product purchasing costs, fulfillment costs, marketing costs associated with promoting the products, and general marketing expenses. It still does not consider overhead costs such as rent, utilities, and salaries. Like Gross Profit 1 and 2, returned items are not deducted in the calculation of Gross Profit

Gross Profit 3

An impression refers to the number of times an advertisement is displayed to users, providing a metric for how many times the ad has appeared on a screen. This term is frequently used in the context of digital advertising and online marketing.

Unlike "views," which are typically associated with video ads and indicate that the ad was actively watched, an impression does not require any interaction or engagement from the viewer. Simply loading the page where the ad is displayed counts as an impression.

For example, if a user sees the same ad multiple times while browsing different pages or over several sessions, each instance counts as a separate impression. This means that the number of impressions can be significantly higher than the number of unique viewers, as one individual can contribute multiple impressions.

Impressions are a crucial metric for marketers to assess the reach and visibility of their ads. They provide valuable insights into the potential exposure of a campaign, helping to gauge how often the target audience is being exposed to the advertising message. High impression counts can indicate broad visibility, but they don’t necessarily measure the effectiveness of the ad in terms of engagement or conversion.

Marketers use impression data to evaluate the overall performance of their campaigns and make informed decisions about how to allocate their marketing budgets. By analyzing the number of impressions alongside other metrics, such as click-through rates (CTR) or conversion rates, businesses can better understand how well their ads are performing and whether they need to adjust their strategies to improve results. This approach helps ensure that marketing investments are optimized for maximum impact and return on investment.

Impression, or a view of something, is often used for ads. It answers the question, “How many times have my ad(s) been viewed?” The term used is not views but Impressions. Views are generally used when it's about video ads. An impression does not require any action by the viewer; one viewer can have many impressions of the same ad.

Impression

A marketing strategy where brands partner with individuals with strong social media following to promote their products or services.

Influencers often operate within niche communities, and their audience usually aligns with the brand’s target demographic. This strategic partnership is essentially a form of paid acquisition, wherein brands gain access to a pool of potential customers who are already receptive to the influencer's recommendations. By leveraging influencers’ established credibility and reach, brands can effectively increase their visibility and awareness within the community.

Influencer marketing taps into key marketing concepts such as social proof and word-of-mouth marketing. Social proof involves using the influence and trust that the influencer commands within their network to endorse a product or service. This endorsement serves as a form of validation, which can significantly impact the audience's perception and willingness to engage with the brand. Word-of-mouth marketing is amplified through influencers who share personal experiences or reviews, thereby extending the brand’s reach and fostering a sense of authenticity.


There can be different goals when working with influencers such as reach, relevance, or resonance.

The generally agreed upon follower size for is as followed :

The other category of influencers can also be key opinion leaders who provide expertise in a specific area and have an engaged audience that interacts with whatever brand that is advertised. All these influencer campaigns can be tracked using the Dema app


A marketing strategy where brands partner with individuals with strong social media following to promote their products or services. These individuals, known as influencers, typically have a niche audience that aligns with the brand's target market. This acts as a paid acquisition of warm leads and increases brand awareness among the community.



Influencer Marketing

The Last Click Attribution Model in e-commerce gives full credit for a sale to the final touchpoint before a purchase. Because of its simplicity, it undervalues earlier customer interactions that could have significantly influenced the buying decision.

In e-commerce, the Last Click Attribution Model is a straightforward approach that assigns all the credit for a sale or conversion to the last touchpoint a customer interacts with before making a purchase. This means that if a customer clicks on a paid ad, an email link, and a social media post before buying a product, the social media post will receive 100% of the credit for that sale. Although this model is simple to understand and implement, it often overlooks the value of earlier touchpoints that may have played a crucial role in influencing the customer's purchase decision.

Last Click Attribution

The Linear Attribution Model in e-commerce assigns equal credit for a sale or conversion to all customer interactions on their buying journey. While it recognizes each interaction's value, it may oversimplify as not all touchpoints equally influence the final purchase decision.

In the e-commerce landscape, the Linear Attribution Model is a technique in which equal credit for a sale or conversion is distributed evenly across all the touchpoints a customer interacts with on their purchase journey. For instance, if a customer clicked on a paid ad, opened an email link, and finally interacted with a social media post before making a purchase, each touchpoint would receive an equal share of the credit for that sale. This model recognizes the value of each interaction in the decision-making process, providing a balanced view of the effectiveness of various channels in the marketing mix. However, it may oversimplify the process, as not all touchpoints may contribute equally to the customer's final decision to purchase.

Linear Attribution Model

A Machine Learning Attribution Model, within the e-commerce context, is a powerful tool that employs machine learning algorithms to accurately assign credit to different touchpoints along a customer's purchasing journey. It surpasses traditional rule-based models, such as Last-Click or Time-Decay, by embracing all available data and statistically crediting each touchpoint based on its influence on conversion. This model is synonymous with a Data-Driven Attribution Model. Both leverage the comprehensive understanding of various marketing channels and strategies' efficacy, thereby assisting e-commerce businesses in smartly optimizing their marketing spend and improving conversion rates.

A Machine Learning Attribution Model, another name for a Data-Driven Attribution Model, within the e-commerce context, is a powerful tool that employs machine learning algorithms to accurately assign credit to different touchpoints along a customer's purchasing journey.