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Youtube SEO: Tips to Increase Your Video Ranking

YouTube SEO generally refers to the optimization process aimed at improving the ranking of your videos and channel on YouTube for relevant topics. YouTube is the second most used search engine in the world. Like all search engines, this platform has its own complex algorithm. By optimizing video content, you aim to increase important metrics gained through YouTube such as subscriber count, website visits, and channel awareness (brand).As with all search engine ranking algorithms, no one knows YouTube’s ranking algorithms exactly. You should optimize your channel page, playlists, metadata, video descriptions, and other key metrics. By optimizing the videos on your YouTube channel, you also improve visibility on other search engines like Google, Yandex, and Bing.What Is YouTube SEO?Before diving into what YouTube SEO is and how to apply it, let’s briefly discuss SEO. If you’re new to SEO, read on!There are many definitions of SEO, but our goal with SEO is to improve the ranking of a web page (not the entire site, since search engines rank individual pages) in search engine results pages, thereby driving quality traffic and conversions to the site.Search engines evaluate the information on websites and pages to display the results that best match a user’s query.Web search engines use their own proprietary algorithms to show relevant content to users. Similarly, social media platforms have their own internal algorithms.YouTube uses different algorithms when showing videos on its platform. Therefore, you need to perform YouTube SEO to get your channel’s videos shown to more users.How to Do YouTube SEO?When doing SEO for YouTube, you should always use transcripts—the text of your video. Including target keywords naturally in the transcript will significantly help your ranking in SERPs. When choosing keywords for YouTube SEO, do thorough research and include them naturally in your video optimization.Here are YouTube SEO tips to increase the ranking potential of your videos: Include your important target keywords in video titles and descriptions, If possible, add captions to your videos and mention keywords in your speech, If you use text overlays in your videos, explicitly include your keywords, Consider adding related videos as cards on your channel, Ensure you select the most relevant category for your video, Use custom thumbnails and include keywords in the image file names, Use tags on your videos and make sure to include your keywords, Add links and CTAs to your videos, When choosing content topics for YouTube, examine Google Trends data. What Is the Logic Behind YouTube SEO?On October 9, 2006, Google acquired YouTube, then a video platform and now the world’s second most popular search engine.Google, YouTube, Bing, Yandex, and all other search engines share one goal: to provide their users with the best possible search experience.For example, imagine you search “SEO Evolution” on YouTube. YouTube’s bots crawl all channels and videos on the platform to show the most relevant result to the user.These bots consider several factors to show the best results.To determine which videos provide a good user experience, bots may test different algorithmic scenarios.They may rank a video with a filled-in title, tags, description, and metadata higher than one without. Videos with sufficient comments and engagement tend to rank above those lacking titles or engagement.The core logic is that the algorithm estimates which content will deliver the best user experience and serves it based on past searches and likes.Your YouTube SEO efforts help your videos rank not only on YouTube but also in Google’s video search results.Boost Your Video Rankings with YouTube SEO TipsEven if you follow all SEO guidelines for platforms like YouTube and Google, complex algorithmic calculations may still affect your rankings.Let’s explore YouTube SEO tips to move your videos up in the search results.Keyword ResearchChoosing and using the right keywords is crucial for Google, YouTube, other search engines, and websites. Keywords help visitors understand the topic of the content.Correct usage of keywords on YouTube helps the platform identify, index, and match your video to user queries.When uploading a video to YouTube, you can add keywords to specific fields like the title, tags, and description—be sure to do so meaningfully.Knowing which keywords to add to your channel videos helps you get discovered and drive more traffic.We recommend starting with YouTube itself for keyword research. Just as with Google’s autocomplete, YouTube’s search suggestions can reveal valuable keywords for your videos.Another method is to analyze competitor channels producing content on the same topic. Check the titles, tags, and descriptions they use.Free tools for YouTube keyword research: Keywords Everywhere: A free Chrome extension that provides monthly search volumes and related keywords on YouTube and Google. Google Trends: Helps you see seasonal trends for keywords. VidIQ: A free Chrome extension that gives statistical insights and keyword data for any YouTube videos or channels. We recommend focusing on long-tail keywords. Although they have lower search volume, they often offer higher reach potential. Highly competitive keywords are harder to rank for, whereas long-tail terms can rank more easily.Create Compelling, Attention-Grabbing Video TitlesTitles are one of the first things users see: they should include your main target keywords. Video titles are a key factor in YouTube SEO and influence visibility in search results.Keep titles around 45–50 characters; you can use up to 100. Include action words and curiosity-inducing phrases.Use Tags to Help RankingContrary to meta tag advice in web SEO, using tags on YouTube is important to rank higher. Tags help define and recommend videos, making them a solid source of channel traffic.YouTube allows up to 120 characters for tags. Include a variety of your target keywords.Write Descriptions That Aid RankingThe description field is crucial for both users and YouTube SEO. Clearly explain the video topic and include your target keywords.You have up to 5,000 characters—use this to include keywords you couldn’t fit in the title.Think of descriptions like meta descriptions: they persuade viewers to watch. Include CTAs and links to your website if applicable, and use timestamp links to highlight key sections. You can also add up to 15 hashtags, but avoid overdoing it.Optimize Your Video File NameYouTube SEO isn’t only about in-platform optimizations. Before uploading, rename your video file to include keywords—e.g., use “youtube-seo-tips.mov” instead of “VID_1234.mov.” This gives the algorithm an early hint about your content.Use Transcripts and CaptionsAlgorithms can’t “watch” videos, but they can read text. Adding transcripts and captions helps your content get indexed and boosts ranking.Transcripts convert spoken content to text; you can generate them manually or via tools. Include timestamps so viewers can follow easily.Create Custom ThumbnailsThumbnails significantly improve click-through rates. In search results, the thumbnail, title, and description are what convince users to watch your video.Choose images that illustrate your topic and overlay text. OCR technology helps YouTube and Google understand the text in your thumbnails.Use End Screens and CardsIf you want viewers to take an action, use YouTube cards and end screens. You can verbally suggest other videos, but cards keep viewers on your channel longer.Cards are visual notifications appearing in the top right—up to 5 per video—to drive clicks to other videos or links. End screens appear at the end to prompt subscribers, video views, or website visits.Professional YouTube SEO TipsHere are advanced tips to help algorithms favor your videos: Keep videos at least 2 minutes long; top-ranked videos average over 10 minutes, Always include your focus keyword in the title, Write compelling first lines in descriptions, Use thumbnails that grab attention, Encourage comments on your videos, Share video links outside YouTube—blogs, email, forums, your website, and social media to drive more traffic. Monitor Your YouTube Analytics ContinuouslyYouTube analytics are key to shaping your SEO strategy. Identify what's working and what isn't.Must-watch metrics for YouTube SEO include: Watch Time: Total minutes viewers spend watching your content, Impression Click-Through Rate: Percentage of impressions on YouTube home/search pages that turned into views, Card Click-Through Rate: Rate at which viewers click your cards, Traffic Sources: Tracks where your viewers come from, Unique Viewers: Estimated number of distinct viewers over a period, Subscriber Growth: Monitors changes in your subscriber count. Tools to Strengthen Your YouTube SEO StrategyUse these tools to enhance your YouTube SEO: Canva: Design channel logos, cards, and thumbnails to boost CTR. VidIQ: A Chrome extension to analyze any channel or video’s tags, watch time, and strategy. TubeBuddy: Helps manage your channel and offers SEO insights like tag suggestions and rank tracking. Ahrefs Keywords Explorer: Delivers keyword, tag, and content ideas to power your SEO. ConclusionIn SEO, the longer users stay on a site, the more valuable it is in the eyes of algorithms—and the same holds true for YouTube.The longer you keep viewers on your channel, the more the algorithm notices.You don’t need expensive equipment or high-end production to rank on YouTube. Focus on creating engaging videos that genuinely help viewers.Use the YouTube SEO tips and recommendations in this guide to strengthen your strategy—after all, platforms like Google and YouTube always prioritize great user experience.

10 Google Sheets Tips That Will Make Your Life Easier

Google Sheets (formerly Spreadsheets), a fully integrated product of Google, is used today in many fields and for many tasks. The widespread use of this tool is due to the usefulness it offers to its users, its compatibility with other tools and programs, and its many functions. In this article, we have given tips on how to use the Google Sheets tool more effectively and efficiently.What Is Google Sheets?Google Sheets is undoubtedly one of the most important programs that make our lives easier, especially if you work in a company that uses Google tools or in an industry where you are constantly interested in dynamic data. Sheets, which is also compatible with Microsoft Excel, is one of the most important parts of Google Docs. It is a type of Spreadsheet with numerous services such as editing complex data, and the possibility of common use thanks to its online-based nature.History of Google SheetsGoogle Sheets is from XL2Web, a web-based spreadsheet application developed by 2Web Technologies, founded by Jonathan Rochelle and Farzad "Fuzzy" Khosrowshahi. XL2Web was acquired by Google in 2006 and turned into Google Labs Spreadsheets. On June 6, 2006, a test version was released for a limited number of users on a first come, first served basis. The limited testing was later replaced with a beta version that was made available to all Google Account holders at about the same time as the release of an official announcement press release.In March 2010, Google acquired the online document collaboration company DocVerse. DocVerse allowed multi-user online collaboration on Excel-compatible documents as well as other Microsoft Office formats such as Microsoft Word and Microsoft PowerPoint. Improvements based on DocVerse were announced and deployed in April 2010. In June 2012, Google acquired Quickoffice, a free proprietary productivity suite for mobile devices. In October 2012, Google Spreadsheets was renamed Google Sheets.If that much general culture is enough, let's get to the tips.10 Google Sheets TipsGoogle Sheets, which allows performing many operations from simple to complex, has many different functions. While some of these functions are very often used and widely known, some very useful functions are not known to everyone. These tips will come in handy to help you use Google Sheets the way it works best for you.1. Dynamic ReportsUndoubtedly, the biggest convenience and the reason why Google Sheets is preferred is that it provides multi-use at the same time thanks to its online-based nature, and dynamic reports and dashboards can be created with internet-connected data sources. Google Sheets is for you, especially if it is of great importance to constantly monitor metrics, such as digital marketing, hourly, maybe minute by minute.If what you've read so far hasn't lit a light bulb in your mind, let's think together. If you have 3 different constantly updated data sources in your hand, if it is important for you to be able to follow these sources instantly and you have to keep track of these files that you have downloaded in different formats on your computer, you can combine these sources in one file thanks to Google Sheets and access their sources with the right methods (more on this one by one in a moment). You can get self-updated reports that you can follow forever, at once.2. Add-onsAdd-ons... In their simplest form, they are user-created scripts that run within Google Sheets, Docs, Slides, and Forms. With these mini scripts, you can get some data you want from free APIs, you can easily do many tasks that you have difficulty doing manually with one click, and you can set up an automation that will rock developers without requiring any coding knowledge.In order to access the add-ons, you can click on the Extensions menu in the top menu and then the Get add-ons section, and select the add-on that suits your needs.Caution: Installing unreliable add-ons can be dangerous for the security of your data.3. importrange, importxml, importhtmlImportrange, Importhtml, Importxml, and more. As their names suggest, these three functions and similar ones allow us to transfer any data we need to Sheet files, stock market data, prices on shopping sites, data in another file, and countless data you can think of. In this article, I will not explain the uses of these functions, but if you want, you can review them from the links below and perform your data import operations according to your needs. Importrange Importxml Importhtml 4. Apps ScriptsApps scripts is a service where you can make all Google-based programs talk to each other, set up unlimited automation, create your own add-ons, and create functions with a little JS knowledge.Again, Apps Scripts, which you can access from the same section with add-ons, reveal a world where we can handle the work that we have been dealing with for hours, maybe in a few seconds.If you are interested, you can start developing excellent projects by reading Google's documentation right away.A little tip: Google apps scripts have a limited run time of 6 minutes, with paid accounts it can go up to 30 minutes. You should pay attention to the working time and efficiency of the projects you create.5. Co-editingWe can say that the most important feature of Google Sheets, which distinguishes it from Microsoft Excel, is co-editing. You can edit the fields that different employees are responsible for on different pages of a table at the same time, inform your teammates with the comments you add, and even solve your instant communication problem from the chat area offered by Google while in the file.In addition, you can control who viewed the file you shared from the Document History section and how often, and you can set deadlines accordingly.6. Google ToolsOne of the biggest benefits of Google's providing alternatives to meet almost all of the most used programs in business life is to be able to make these applications talk to each other and automate many processes easily. For example, let's say you update data from the same tables to the same presentations every week. Thanks to the Google Sheets and Google Slide connection, you can automatically update your presentation when you just update the table, by connecting the tables you need to the appropriate Slide tables and get rid of extra workloads.Or, you can send the data sheets that you regularly mail to as often as you want by connecting to Google Sheets - Gmail without having to deal with it over and over again every day.In short, you can have all Google's tools talk to each other, facilitate the processes you deal with from place to place, and use your time much better.7. VlookupVlookup is perhaps one of the most important Google Sheets functions that allow us to match data in different rows in two different data tables. For example, you have user_id data and session metric in one table, and label information corresponding to these ids in the other table and you want to match them. For a file with thousands of rows, it may take days to do this manually! With vlookup it will take 15-20 seconds.=VLOOKUP(search_key, range, index, [is_sorted])For more detailed information: Vlookup8. QueryLet's come to the most crucial point of the article and my clear favorite function: Query. With this function, with a syntax similar to the SQL language to organize and report your datasets, you can do things that are really complex and much easier than you can do using the & feature of Sheets 4-5.Syntax=QUERY(data, query, [headers])As you can see, let's write a small example formula of how we can use this function with only 2 mandatory parameters. Let's say the operation we want to do is as follows: By examining columns A, B, C on the "Data" page, we want to select the numbers in column A that are greater than 10 and also the cities in column C that are "Ankara", and the results of this query are larger than column B. Let's sort them in descending order.=QUERY(Data!A:C,"SELECT A,B,C WHERE A>10 AND C<>'Ankara' ORDER BY B DESC",1)9. IFSIf, sumif, countif, maxifs, minifs, dateif, iferror... As it can be understood from the if pattern, functions with ifs allow us to perform operations on most conditional situations. At the same time, it is very important to know what we need to be a good Sheet user and to practice using it. . That's why we need to know what functions with ifs are and how they're used.Let's look at a small if example together: We want to distribute letter grades such as A,B,C,D according to the scales of grades received by students in a class, then simply: =IFS(A3>89.99,"A",A3>79.99,"B",A3>69.99,"C",A3>59.99,"D",A3>0,"F")Or, if we want to aggregate sessions in column B where the sources in column A are "google":=SUMIF(A:A,"google",B:B)For more detailed information, you can review the contents in the links below. Sumif If Countif Maxifs Minifs 10. MacrosFinally, Macros, one of the most important features of Sheets, which we can define as a lifesaver, especially for users who are tired of repeating the same manual operations every day. Macros, which can also be accessed from the extensions section, is an application area where you can repeat the UI operations you will save as often as you want, and it works based on Scripts.In fact, to summarize simply, it allows you to perform operations such as copy-paste and insert rows that you do every day in the format you specify, and has numerous uses.From Google's developer document, you can examine the usage areas, record your macro according to your own needs, and automate the processes you spend hours every day in a few seconds.You can access the Macros document here.In addition, from the Google function list page, you can review all functions, find the ones you need, and expand their usage areas.

What Are Performance Marketing Metrics? The 15 Most Commonly Used Metrics

Marketing metrics play a crucial role in interpreting the campaigns we launch and the ads we create. It’s essential to derive insights from the data we have and take action accordingly. Accurately analyzing a campaign’s metrics and taking the most effective actions during this process is critical.Misinterpreting performance success—whether through missing or incorrect analysis—can lead to mistakes in judging whether our campaign is performing well, causing both short- and long-term missteps. In this article, we’ll share tips on how to correctly interpret the most frequently tracked and most important metrics in performance marketing.What Does “Metric” Mean in Performance Marketing?Marketing teams use measurable figures called marketing metrics to show the success of campaigns and projects across all channels. Examples include Conversion, CTR, and ROAS.What Is a Conversion?When creating a digital marketing campaign, every brand has one or more goals that motivate users to take action. All marketing efforts are ultimately aimed at achieving these goals.A Conversion is the metric that counts how many times a specified goal is achieved within a website, page, or mobile app. For an e-commerce company, this metric might be the number of sales; for a consulting firm, the number of leads (form submissions). A high conversion rate indicates your ad campaign is successful and your landing page content is compelling.If your conversion count is low, you might improve it by changing site content, creating new funnels to simplify the conversion process, or updating offers to provide a more effective experience for users.What Is Conversion Rate?Conversion Rate measures how often conversions occur as a result of your ads. It shows the percentage of ad interactions that turn into your defined conversion goal. By looking at conversion rate, you can optimize landing pages, calls to action, content, and design, and gauge how compelling your ads are to your target audience. Conversion Rate is calculated by dividing the number of conversions by the total number of sessions. For example, if an ad generates 300 sessions and 10 conversions, the conversion rate is 3%.What Is Conversion Value?Conversion Value assigns a numerical value to specific conversions in your campaigns, helping you measure how valuable those conversions are to your business. By assigning different values to different conversions, you can make your campaign’s value measurement more meaningful. You can compute Conversion Value using the formula: Sessions × CR × Average Order Value.For example, if a shoe retailer has 10,000 sessions, a 1% conversion rate, and an average order value of 1,000 TL, the Conversion Value is 100,000 TL.What Is CPC?CPC (Cost Per Click) simply shows how much you pay for each click. Because you pay per click, irrelevant users clicking on your ads increase your unnecessary costs and raise your total spend.CPC is one of the key metrics for evaluating campaign performance. To lower CPC, you can optimize ad relevance, switch bidding strategies, and target the right keywords through analysis.What Is a Session?In digital analytics, a session measures a user’s interactions on a website within a given time frame. A session begins when the site loads and ends when the user closes the site or is inactive for 30 minutes. It encompasses pageviews, events, and other actions the user takes.To increase session duration, enhance site experience—improve design, readability, navigation, and content to keep users engaged and complete your desired conversions.What Is CPS (Cost Per Session)?CPS measures the cost of each session driven by your ads. Since sessions reflect active user engagement on your platform, Cost Per Session shows how much each session costs based on your ad spend.What Is ROAS?ROAS (Return on Ad Spend) measures your ad performance in terms of cost versus revenue. It represents the profit you earn for every unit of currency spent on ads. Since brands aim to get a strong return on investment, tracking ROAS provides powerful insights into campaign success.For instance, even if an ad brings in many high-quality users and revenue, it’s not a cost-effective spend if the cost exceeds the revenue. ROAS tracking helps you avoid such scenarios.What Is CTR (Click-Through Rate)?CTR measures the percentage of ad impressions that result in clicks. It indicates how relevant and compelling your ads are to your target audience. A high CTR is critical in PPC, as it affects Quality Score and indirectly the cost per click. Google Ads and other platforms reward high-quality ads with lower costs.If a competitor pays the same CPC but has a lower Quality Score, you may pay less to achieve a higher ad position. You can boost CTR by including search terms in headlines and descriptions, adding URL paths, and targeting the right keywords.In display campaigns, where creative visuals matter most, CTR offers insight into the effectiveness of your creatives.What Is a Lead?In marketing, a lead typically refers to a form submission generated by your campaigns. Each lead represents a potential customer. However, a high lead count doesn’t always mean campaign success—lead quality matters most. That’s why defining your buyer persona and targeting accordingly is crucial.To convert leads into sales, provide personalized content, maintain close collaboration with your sales team, and guide users along the funnel.What Is CPL (Cost Per Lead)?CPL measures how much each lead costs you. It shows whether you’re allocating your budget effectively. By comparing CPL across channels, you can reallocate budget from high-CPL channels to those generating leads more efficiently.CPL = Total Ad Spend / Number of Leads.What Is Search Impression Share?Search Impression Share is the ratio of impressions you received to the total impressions you were eligible to receive. Eligibility depends on factors like audience targeting, approved ads, bids, and Quality Score. For example, a 50% impression share means you appeared in half of the available auctions.If your impression share is low, you’re missing potential customers. Increasing impression share relies on high Quality Scores, sufficient bids, and adequate budgets.What Is Top Impression Share?Top Impression Share measures how often your ad appears above organic search results. If you notice your click-through rates dropping, it may indicate you’ve lost a top position.What Is Absolute Top Impression Share?Absolute Top Impression Share is the percentage of your total impressions that appear in the very top ad position. It’s calculated as impressions in the top position divided by the estimated eligible impressions for that position.What Is Bounce Rate?Bounce Rate is the percentage of users who leave your site after viewing only one page without taking any action. Tracking bounce rate helps you assess site experience. A high bounce rate can signal issues such as irrelevant content, slow loading times, or poor mobile optimization.To lower bounce rate, define your audience accurately, optimize page load speed, and use clear, compelling CTAs.Bounce Rate = (Single-Page Sessions / Total Sessions) × 100.What Is Frequency?Frequency measures how often a user sees your ad. Multiple impressions can help undecided users purchase, but if they see the ad repeatedly without converting, you may need to broaden your audience or adjust spend.Very high frequency can annoy users and harm your brand. Expand your targeting or reduce budget if frequency is too high. Ideal frequency varies: it’s lower for new-user campaigns and higher for remarketing. Determine your target frequency by reviewing past campaigns to find where CPA was minimized.

Market Basket Analysis

In today’s world, after the very well known pandemic we had through, the e-commerce sector rose like the sun. With this raise, websites of almost every brand from relatively small businesses to the largest businesses have gained a lot more popularity and their traffic has increased almost 50%. According to the International Trade Administration (2021), an average of 19% increase in e-commerce revenue is forecasted (26% in Food & Personal Care products) after the pandemic.These growth statistics and developments tell us one significant thing that the businesses should start to give more attention (and more budget) to their e-commerce/marketing departments and their operations. When e-commerce is mentioned, the first thing that comes to mind is obviously websites. Products are being tried to be exhibited in websites in such ways that help business owners to sell more products and gain more revenue from their most valuable resources which are customers. There are tens of ways to take the attention of customers and give them the intent of simply buying more. In this article, I will try to explain a method called “Basket Analysis”.What is Basket Analysis?Basket Analysis is a method that research and study on the baskets (carts) of customers in the website and analyse them to offer meaningful and customised product suggestions to the customers. Before getting through to the technical part of the analysis, there are some more things that we should better mention. Every customer is different as well as their purchase behaviour. Every product is different. However, some of them are used and bought together. In some situations, very unrelated products are sold together and human eyes sometimes cannot determine these ones. Exactly here, artificial intelligence and machine learning enter the stage.Let’s dive deeper into algorithms.Apriori AlgorithmThe Apriori algorithm has been in our minds since 1994 and it helps us find frequent item sets in a dataset for boolean association rules. Name of the algorithm is Apriori because it uses prior knowledge of frequent item set properties.In this algorithm, as mentioned above, the dataset must include products that are frequently bought. The data we need to apply this algorithm includes the following columns: Transaction ID (Basket ID) Product SKU (Product ID) Product Category Quantity After we obtain the necessary data, the magic starts.This algorithm can be written and applied by R Studio, Python etc.Since our data is breakdowned and thus has duplicate transaction ID’s, first we need to group the data by transaction ID and learn every distinct product that has been sold (obviously added to basket before the payment step) in that specific transaction.After this is done, we get dummy variables of all products and create new columns for each of them. For every unique transaction row, the quantity of the product is written to the cell of its own column and transaction. A sample processed data can be seen below:Transaction IDProduct AProduct BProduct CProduct D123abc7300456def2011Machine learning has its own rules, obviously. In order to analyse this data and have meaningful insights, we need to encode the cells into 1-0 to determine which product is added to the basket and bought in that specific transaction. The reason to do this is that Apriori Algorithms takes only 1 and 0 values to determine the association between products without any bias such as unrelated quantities. Consider that we are only interested in products that are being sold together.Finally, before we apply the model, we yield the below data:Transaction IDProduct AProduct BProduct CProduct D123abc1100456def1011We use the “frequent_patterns“ tool from “mlxtend” library and import “apriori” and “association_rules” packages to apply the model in an optimised and fast way.After the necessary parameters are adjusted in the model according to the specific dataset and specific purpose, we get the results as a table below:AntecedentsConsequentsAntecedentSupportConsequentSupportSupportConfidenceLiftLeverageConvictionProduct AProduct B0.40.60.50.832.780.0221.67Product AProduct C0.40.30.450.652.110.11.12Product BProduct D0.60.50.50.621.98-0.321.43Note: Values are randomly generated due to privacy issues.Results:OK. But What do they Mean?Here, the most important metrics that we should consider are “support” and“confidence” values. However, you can read the explanations below for a better understanding. Antecedent Support: The rate of the presence of antecedent products over all. Consequent Support: The rate of the presence of consequent products over all. Support: The rate of presence of antecedent product and consequent product being together in basket over all. Confidence: The confidence rate of products’ being together in the same basket. Lift: Confidence over expected confidence. Leverage: The statistical independency rate of a specific basket according to including products in it. Conviction: Gets higher when the consequent product is highly dependent on the antecedent product. After we yield the result table, we can start to analyse the results. How we do this analysis is according to some statistical methods. We should determine a threshold value for the “confidence” metric and split the rows into two parts: Meaningful or Not.When the confidence value is more than the threshold value, say 0.6, we can conclude that this relationship between products is meaningful and customers frequently buy these products together. Where to Use these Results? Where to use these results is another challenge.Businesses usually use this information for suggestion algorithms and shelf design. For instance, Product B is suggested to the customer who has just added Product A to his/her basket because the confidence level of these products is higher than our threshold value. Thus, the possibility of customer’s missing, forgetting or just not being interested in Product B is decreased and thus, we are being able to direct the customer to buy Product A. Secondly, shelf design (product listing pages in our case) can be conducted and applied to our website according to the results. For instance, Product A and Product B are located near each other to remind customers that they can buy them together (because they generally do it, don’t they?!).Thirdly, campaign scenarios can be set up for customers. For instance, Product B is presented with discounted prices for those customers who add Product A to their baskets or simply buy them before. Last but not least, the results of this analysis can help the business owners and marketers to design their offline (physical) stores’ shelves. Just like the product listing pages in websites, stores shelves can also be designed in such a way that customers can see related and frequently bought products together. In these ways, sale amount, order amount, revenue, traffic that website gains and key performance indicators like these may be increased. Besides, product & marketing costs can be allocated according to the results.

Product Scoring Algorithm

You are curious about performance of your products. And also, you are worried about how you can manage your product scope to increase revenue. Here are the answers for all of your questions, check out our blog and learn about our product scoring algorithm.Common problems in product managementThere are a number of questions that professionals might have in their mind while evaluating their companies’ performance. And some of these questions are more beneficial when thinking about important actions to increase efficiency of products that are sold on websites, apps and marketing channels.Here are some “general” questions that each team might be curious about the answers to. Which e-commerce metrics should we focus on while considering inventory management? Which products are more valuable? How can we increase our revenue by having the same product scope? What should be our key metrics for optimising marketing campaigns of our products? How should we decide our product listing in our website or app? Yes, you are right! AnalyticaHouse Data Science & Insights Team have another magical algorithm that would be helpful for all mysterious questions above and more, which is Product Scoring Algorithm. In this article, we will be talking about the structure of this algorithm and applications of it in the digital marketing sector.How is the algorithm built?There are a lot of variants for product groups in each website and app differentiating based on various dimensions such as colours, sizes, product types, season/offseason, target genders, target age groups and so on. We would be able to analyse every detail of products and product variants thanks to the Product Scoring Algorithm depending on the depth of the data we have.The minimum data requirement for this analysis are transactional data of products and current inventory information of them. We are focusing on these metrics while analysing transactional data; number of purchases, total quantity, revenue, average price and so on. Of course, this analysis would be more interesting when we have user/session-based data. We would be able to add other important metrics such as product detail views, add to cart, # of buyers, # of users who look at the product, revenue/product detail views, transaction/product detail views and so on. These metrics can be grouped into parts according to results they show; Revenue supporting metrics : number of purchases, total quantity, revenue, average price, revenue/product detail views, transaction/product detail viewsMetrics that show customer interest : product detail views, add to cart, # of buyers, # of users who look at the product, revenue/product detail viewsMetric definitions number of purchases: Number of transactions Total quantity:  Number of products that are purchased Revenue: Total amount of revenue Average Price: Average price of products revenue/product detail views: Revenue per product detail views for each product transaction/product detail views: Conversion rate (based on product detail views) add to cart: Total number of products that are added to cart # of buyers: Total number of customers who purchased related product # of users who look at the product: Total number of users who viewed related product Application of the modelThe algorithm can be applied to each product level and can bring insights for bigger picture and tiny details.The example below shows a category/product level for an e-commerce company; Level 1: Shoes/Bags Level 2: Shoes Level 3: Sneakers Level 4: X Brand’s Sneakers Level 5: X Brand’s White Sneakers Level 6: X Brand’s White Sneakers with Size:38 How is product score calculated?Product Scoring Algorithm is basically formed from two parts. The first part is based on calculating ratio of lower levels (eg. X Brand’s White Sneakers with Size:38) in totals of higher levels (eg. X Brand’s Sneakers) by using metrics that we discussed above, and we will explain this part by showing an example. The second part is dependent on current inventory information of products, and this part is very crucial when we take inventory management into account for short term and long term.  Example above shows a product scoring calculation by using metrics add to cart and quantity sold in addition to instant inventory score ( if there is inventory it is 1 and if not it is 0). In this example distribution of level 6 in total of level 5 for add to cart and quantity sold metrics and inventory score are used as three multipliers of product score of level 6.  After calculating the score of each row (each breakdown, for this example it is level 6), we calculate the score of the higher level ( in this example it is level 5 ). We take the sum of the score of all breakdowns for level 5 and as a result we have the total score of level 5. For example; for X brand’s White Sneakers the total score can be calculated as :0,0747 + 0,0245 + 0,0036 + 0,0028 + 0,0251 + 0,0000 = 0,131In this example X brand’s Black Sneakers has the highest score (0,193) and X brand’s Red Sneakers has the smallest score (0,071).How can we use the results?This analysis can be applied to all levels from bottom to top. And of course, this analysis can be enlarged with additional metrics that we talked about before and results can be calculated in more detail. In addition to that, we can change the importance of each metric in the calculation step of the product score by using Variable Importance Analysis which is another outstanding algorithm that our team improved. Last but not least, results of the analysis can be used for updating product feed automatically for marketing campaigns.