When Is Third Trimester Ultrasound Done, Dewalt Dcs361 Blade Change, Preloved Model Boats, Property Maintenance Duties, Preloved Model Boats, I'll Give You Everything Babyface, Scb Uae Customer Care Email Id, Nichole Brown Age, Farce Charade Crossword Clue, Rockstar Dababy Guitar Tabs, advertising" /> When Is Third Trimester Ultrasound Done, Dewalt Dcs361 Blade Change, Preloved Model Boats, Property Maintenance Duties, Preloved Model Boats, I'll Give You Everything Babyface, Scb Uae Customer Care Email Id, Nichole Brown Age, Farce Charade Crossword Clue, Rockstar Dababy Guitar Tabs, advertising"> data science methodology case study email When Is Third Trimester Ultrasound Done, Dewalt Dcs361 Blade Change, Preloved Model Boats, Property Maintenance Duties, Preloved Model Boats, I'll Give You Everything Babyface, Scb Uae Customer Care Email Id, Nichole Brown Age, Farce Charade Crossword Clue, Rockstar Dababy Guitar Tabs, …" />

data science methodology case study email

If you suspect a measurement issue, try slicing subscriber activity by email client. Stacked Histogram: Ever Opened vs. Never Opened by Joined Time, Inactive Subscribers are New but the Majority. Figure 5c Discussion: It is important to note this graph shows on the x axis the date of when the latest email was opened (as opposed to date the email was sent). Latest posts by Manu Jeevan . Accessed June 7, 2017. http://www.lse.ac.uk/media@lse/Polis/documents/Back-to-the-future—Email-Newsletters-as-a-Digital-Channel-for-Journalism.pdf, [2] Doctor, Kenneth. Data Science in Pharmaceutical Industries. Exact statistics on mobile email reading behavior vary based on audience and type of email, but multiple studies show more than half of email opens are on mobile devices. The case study approach sits well with this, but you still need other methods to draw your research and action together into the story and meaning you convey through your case study. Proportion of List Cleaned by Time Joined, Mature List. Figure 2d. Cleaned addresses typically compose the smallest cohorts. Further research is needed in the following areas: Delineating peer groups for metric comparison, incorporating additional features related to retention and revenue, and exploring more sophisticated forms of analysis such as hidden Markov models (HMM). The team analysed 30 transactional email templates for emotional content. The notebooks are a jumping off point. And if so, does that mean theoretically open rates can be higher than 100 percent? To begin, we will explore the most basic example of Predictive Analytics: A/B Testing. It is essential to have a clear understanding of the calculations behind the metrics provided by your email service provider. Is a certain group of readers turned off by your content? Some of the spikes in the fraction of cleaned readers are concerning, such as in late 2014, where 40% of all emails acquired at that time have been cleaned. Data Requirements: The above chosen analytical method indicates the necessary data content, … Unique Open Rate Distribution for Subscribers, Struggling List. Any email from a certain address or from a pattern of addresses is spam. All emails include an unsubscribe link. Stacked Area Graph, Last Active. Lifetime subscribed, unsubscribed and cleaned rates help paint a high level picture of churn and subscriber retention. The y axis represents counts of the number of unique email addresses. Additionally, “Clicks per unique opens” and “total clicks” are presented. Predictive Intelligence and Predictive Marketing, Smart Insights (Marketing Intelligence) Ltd. [2] A hard bounce is an email message that has been returned to the sender because the recipient’s address is invalid. Below we are going to outline 3 techniques you can implement from ‘getting started’ lists of around 500 subscribers, to highly advanced models geared towards enterprise users. I have described such a methodology: the Foundational Methodology for Data Science, depicted in the following diagram. Possible implications include: [4] If your email service provider cannot show this kind of behavior, by pulling the raw data you have the tools to run more accurate campaign reports and can even automate this process to report by various segments (perhaps even paid, unpaid, time on site, etc). The table below presents the nuances of how three commonly used email service providers label, define, calculate and display open rate and click rate metrics. This report is not intended as a "how-to" for con-ducting case studies, but rather is a recognition of important points to be taken into account by people conducting this kind of research and for people who read the results. Data analysis holds the key to building revenue sustainability—the bedrock issue for any enterprise—in our increasingly digital world. Section 1: Depicts the process of pulling data from the MailChimp API. The IP reputation of your sender is poor or the email is not sent from a verified domain (SPF/DKIM). The standard “open rate” metric tracks the percentage of users who have opened an email. The Shorenstein Center Notebooks are a way to help with both, with the hope that information gleaned from email acquisition and larger audience analysis can be used not just to hone an email strategy, but to inform new products, platforms and revenue streams. A data science framework has emerged and is presented in the remainder of this article along with a case study to illustrate the steps. “To be invited into a place where people live—and to know you won’t be filtered by an algorithm—is a very powerful thing.”[3]  Swedish journalist Charlotte Fagerlund adds: “Emails have got quite a lot of different functions. News organizations are slow to this game. A data science framework has emerged and is presented in the remainder of this article along with a case study to illustrate the steps. “Back to the Future- Email Newsletters as a Digital Channel for Journalism.” Polis, London School of Economics, January 25, 2016, 1-16. Unlike many other digital channels, email allows publishers to measure repeat, sustained reader attention. The result was a click through uplift from 13.4% to a predicted click through rate of 23.7%. 1. Business understanding The example in Figure 7a shows a list with highly engaged subscribers, the majority of whom have been on the list a longer time. Figure 4c Discussion: In Figure 4a, user unique open rate bins taper somewhat gradually left to right. The several variables are referred to as Predictor Variables, while the individual variable they’re fitting against is called the Response Variable. Aim: To illustrate an approach to data analysis in qualitative case study methodology. Watsi, for example, uses email to support their product. Fig 1: Data Science Process, credit: Wikipedia. For the last couple of weeks we have been working on a marketing analytics case study example (read Part 1 and Part 2).In the last part we defined a couple of advanced analytics objectives based on the business problem at an online retail company called DresSmart Inc.In this part, we will perform some exploratory data analysis as a part of the same case study example. Very basically, the larger the sample size, the more statistically significant (meaningful) the results will be. The Notebooks mark a change in mindset from accepting pre-determined metrics to exploring and defining more pertinent and relevant measures for modern news media. Every Data Scientist needs a methodology to solve data science’s problems. ... you can also write an article using contribute.geeksforgeeks.org or mail your article to [email protected] See your article appearing on the GeeksforGeeks main … MobLab, a network for social change campaigns, published a series on this subject starting in 2013. Many people contributed in various ways to this paper, including Emily Roseman, David Beard and Nik Iubel. The Shorenstein Center Notebooks represent the first step in our call for new reporting standards for email, and for larger audience analysis. The methodology of data science begins with the search for clarifications in order to achieve what can be called business understanding. By plotting the true … View larger. There is some debate over how long inactive subscribers should remain on the list before removal. In this situation, another technique has to be introduced which assess the correlation or association between variables. Figure 3b. Figure 4b Discussion: This example shows a list where many subscribers open 80-100% of all emails received, representing an extremely engaged audience. To better examine trends of how user engagement fluctuates, the next visualization examines the same data by looking at the proportion of everyone who joined during a certain time and segments individuals by the time of their latest email open (12 months, 9 months, 6 months, 3 months, 1 month). Additional investigation would include looking at this data over time. The x axis represents the time joined—time the user record was created. Figure 6b Discussion: The peaks and valleys in this graph show that some acquisition campaigns yield stronger engagement than others. You have recently joined in as the chief analytics officer & business strategy head at an online shopping store called DresSMart Inc. that specializes in apparel and clothing. Lists older than 5 years may have higher cleaned rates, between 10-15%. Contributions are welcome. Figure 7e shows that a greater number of older users on the list have unsubscribed compared to newer users. Figure 4b. One possible approach is sending additional emails requesting that users confirm subscription. Though fictionalized, the Princeton Dialogues case studies were developed from examples of existing AI technologies. Are you targeting and acquiring the wrong audience? Another common challenge of focusing on list size is the connotation that unsubscribes equals failure. Most opened an email recently (farther up the y axis = more recent open). For every 100 subscribers who successfully joined the list: where s, u, and c are the number of users expected in each state. A Report from the Shorenstein Center’s Single Subject News Engagement Project. These analyses are often custom fields and, while the notebooks can be incorporated into this type of analysis, that is beyond the scope of this guide. Figure 7a. Whether a company wishes to compare the performance of two email templates, compare the performance of multiple email templates or see the association between several characteristics of an email and a single metric, Predictive Analytical techniques allow them to acquire the answers they need. The latest email opened by unsubscribed users is distributed over the lifetime of the list, with a greater concentration of latest opens in mid-late 2017. Furthermore, 80% of all current subscribers acquired in February 2017 have opened an email in the last 12 months, whereas less than 40% of all current subscribers acquired in August 2017 have opened an email. Case study methods … We will get a better understanding of the above process in the following case study. The notebook code is fully available on GitHub and are built on top of open source libraries, making all calculations and manipulations fully transparent. Time of the Last Email Opened vs. Time Joined, Current Subscribers. NOTE: Figure 7d only displays information for current subscribers who have opened at least one email. It is possible to find legitimate subscribers stuck in pending. 4 successful data science case studies. Do you need a better welcome series? Summary statistics in Section 3.2 are helpful to begin painting a picture of list composition, but they do not provide any insights regarding your list composition by time joined. letters, study … [2] “Email is such a powerful delivery tool because it’s a stream people already check,” says Ben Thompson, founder and author of the popular tech newsletter Stratechery. In this example, the predictor variables were the purchases the customers made, while the response variable was whether a customer was pregnant or not. SAGE Research Methods Video contains more than 125 hours of video, including tutorials, case study videos, expert interviews, and more, covering the entire research methods and statistics curriculum. Media companies use email to push readers in massive numbers to websites, convert their readers into paid subscribers and then maybe even purchasers of related events and products. Figure 2c. Seemingly minor changes to email client products, such as Google priority inbox, carry vast implications and can have outsized effects. “Who’s LOLing now?” Traffic Magazine, September 2016, 22. Additionally, other file types, such as json, excel, csv, etc., can be imported into the notebooks if desired. For all emails acquired on that date, currently a greater fraction are unsubscribed than subscribed. One approach is to examine the lifetime of the list. Sometimes a case study will also collect quantitative data. Are your emails too frequent? Applied Data Science. When newsletters become a business, it’s worth paying careful attention to their strategy. Conversely, a high proportion of unsubscribed users who are least engaged, with user unique open rates between 0-10%,[5] is common among lists with good hygiene. [1], Email newsletters are now the mechanism for engaging and retaining readers and converting an audience into paying subscribers or moving them toward other sources of monetization. Deliverability (making it to the inbox), effective deliverability (readers see your email in their inbox), and measurability (extent to which reader opens or clicks are recorded accurately) bring a degree of uncertainty to some measures of performance. The key is knowing how to leverage and manage the email newsletter correctly. While this is largely true, it is important to understand the gray areas of email. [5] How can someone who has never opened an email unsubscribe? It functions almost like a physical address. We want to especially thank the individuals who contributed to and supported: Jupyter notebooks, pandas, and matplolib are all open source tools in python that have been built by the open source community with support from NumFOCUS.org. 1. The ambiguity of “open rate” (rather than specifying unique open rate vs. total open rate) is just one example of how traditional email analytics can be misleading, and illustrates the need for an industry-wide clarification of reporting standards. 2. Figure 7a and 7b Discussion: To better understand how to read the joint distribution in Figure 7a (User Unique Open Rate vs. Time Joined) refer to Figure 7b. The remainder of the list is more engaged, and a small portion has opened between 80% and 100% of emails received. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. Let us now consider the case study … Performance could be measured by anything the business is interested in; Open Rates, Click-Through Rates (CTR), Engagement, Conversions etc. Matplotlib and seaborn are used for data visualization. Case Study Methodology. Figure 2d Discussion: Figure 2d visualizes the same list as Figure 2c, and represents a case where cleaned emails could have been plotted on the same y axis as the three other possible states. Case Study Example – Marketing Analytics. Banks have to realize that big data technologies can help them focus their resources efficiently, make smarter decisions, and improve performance. Looking at the distribution of individual user open and click rates provides another vantage point for these familiar metrics of audience engagement. Empirical foundations. [3] Davis, Noah. While ad units in email tend to have higher CPMs (cost per thousands), email is a primary source for reader revenue through subscription or membership programs. Figure 2c Discussion: Although atypical, this example can be extremely informative about the longer term outcome of acquisition efforts. These spikes may be associated with ineffective acquisition campaigns and need to be further explored. Case Study Helper by No1AssignmentHelp.Com - A case study is a record of research into the development of a particular person, group, or situation over some time. Accordingly, in this course, you will learn: - The major steps involved in tackling a data science … If a reader was pending, then subsequently became a subscriber by completing the second step of the double opt in process, the current status is subscribed. Figure 2b Discussion: Over the lifetime of the list, the largest fraction is subscribed, except for one time period. This article defends case study methodology as an appropriate methodology, giving a description, the process and its strengths and weaknesses. “Click Through Rate” is labeled “Clicks / Opens” on the main dashboard. The example in this visualization may seem low because of the dramatic drop-off in the click rate, but given the equation (user unique click rate = number of unique clicks / number of emails received) this distribution will be common. See our privacy policy and terms & conditions for your rights under GDPR, My clients love the insights I am now capable of providing them, Just like having an expert working by your side, - Sharon Sheridan, Digital Marketing Manager, It's made my digital marketing tangible, measureable and actionable, - Kirsty H, Director of Content and Brand, Presentation Studio. This guide includes an overview of data science and it also includes real-life case studies… Need a plan to create a winning marketing strategy, fast? Taking this approach begins to uncover audience trends throughout the lifetime of the list. In this example, the shortest time was 16 hours while the longest tenure on the list was 400 days. Unique Open Rate Distribution for Subscribers, Very Engaged List. Case study research is a qualitative research method that is used to examine contemporary real-life situations and apply the findings of the case to the problem under study. As long as raw audience data can be collected, updating the Shorenstein Center Notebooks for compatibility beyond MailChimp requires relatively trivial changes to achieve the same outcomes. Other digital communicators shifted years ago to this deeper level of analysis. So now, let's look at the case study related to applying Data … Current subscribers who have not opened an email are not represented. With better control of overall data, a more accurate version of the statistics can be calculated. Unlike the web, the actual amount of time spent reading an email is not easily trackable. Case study method of Data Collection According to H. Odum, “The case study method of data collection is a technique by which individual factor whether it be an institution or just an episode in the life of an … The Shorenstein Center notebooks are the beginning of our work, our first tangible contribution to the field. Welcome to Data Science Methodology 101 From Understanding to Preparation Data Preparation - Case Study! Newer subscribers have a bimodal distribution. Figure 7d. Figure 3a Discussion: The results for this list show that inactive subscribers have recently joined the list, and that these inactive subscribers are a relatively small portion of the list. Is there a way to move more subscribers to greater engagement? A brief review o f design research focusing o n its Cleaned is broken out on a separate visualization because in many cases the scale of the y axis is small compared to subscribed, unsubscribed and pending, variations in cleaned are hard to see on the same scale as the others. Our initial research suggests that a proportion of 15% cleaned or above is high enough to warrant further investigation. With that, comes a few things we would like to note For example, MailChimp’s reported “click” rate is much lower than Constant Contact’s “Clicks (Click-Through Rate)” because ultimately they are based on different calculations. There are many ways of looking at subscriber churn. Is most of your list deeply engaged with your content, or does a tiny minority represent most of the list activity? Importantly, the unsubscribes may have happened over time. Among all the potential uses of smartphones, reading and writing email is the third most popular activity after text messaging and web surfing—it even tops listening to music. Data Collection: Beyond readability, there are some challenges in email with data collection. Figure 7f. Reading a joint distribution: Start with the x axis, and corresponding one-dimensional smoothed histogram at the top of the visualization, which in this case represents the volume of subscribers by the time each joined the list. List Composition by Date Joined, Expected Cleaned. Inevitably, subscriber email addresses will be cleaned over time for a variety of reasons. Or the paper, if you want an abridged version, which comes out of it. The single most reliable digital channel for building a “habit of news” is email. Re-engagement campaigns should be run to move inactive subscribers toward greater engagement, and the proportion of inactive subscribers on your list should be monitored regularly. Examining subscriber activity in this manner can help hone future acquisition campaigns. The list in Figure 4c has a high number of relatively inactive subscribers (0%-10% unique open rate), and a low number of current subscribers with user unique open rates greater than 10%. DATA SCIENTIST INSIGHTS Using Data Sciences and Artificial Intelligence to Explore the Darkest Places on Earth - Data Many scholars have argued that the social sciences rely too heavily on quantitative research and formal models and have attempted to develop and refine rigorous methods for using case studies. The purpose of this paper is to introduce key methods of email data analysis and argue for new metrics that measure audience engagement. NOTE: A user unique open rate of 0 can only be achieved if the subscriber has never opened an email. This first notebook examines the composition of your email list as a whole, and slices the data to reveal new insights and areas of inquiry. Turns out, Raj employs an incredibly helpful framework that is both a way to understand what data scientists do, and a cheat sheet to break down any data science problem. Therefore, new lists start off with no cleaned subscribers. a tool, a piece of furniture, or even computer printout. Documents e.g. Readers who sign up for the New York Times’ email newsletters are twice as likely to become subscribers. The analysis was then compared to the CTR that each template received from millions of EasyJet customers. Most email service providers today define open rates as the percentage of users that open delivered emails (we call these “unique open rates”), but some providers compute it as the number of times delivered emails are opened, allowing multiple opens by a single recipient or forwards to be factored in (we call these “total open rates”). Python IDEs for Data Science: Top 5 - January 19, 2019; The 5 exciting machine learning, data science and big data … To do this, providers need to consistently make excellent operational decisions, as these other industries have. A software package based on Microsoft Access is AnSWR that is suitable for the analysis of qualitative data … Larger bars on the right hand side of the graph show significant recent engagement of the list. Combining data from the x and y axis creates the contour plot in the center; which in Figure 7a shows a concentration of subscribers who have been on the list for a longer period of time, with very high open rates. Unless the list owner unsubscribed inactive subscribers, the last email opened by an unsubscribed user will be the email the now unsubscribed user opened as a subscriber, before taking the unsubscribe action. Figure 4a Discussion: This example shows a list where about a third of subscribers have opened between 0% and 10% of emails received. The analysis in this section plots the current status of all unique email records by time joined—the time the user record was created. Because we cannot show two different email templates to the same group of people, it must always be remembered that it may not be the design of the template that’s driving changes, but rather the personality, motivations, time available and aims of the people who received those emails. A simple, straightforward number is useful to assess trends, but provides very little insight into the quality of the list or the list’s engagement. Of a traditional performance funnel puts pressure on large list growth and can have outsized effects list removal... Researchers to study a case can rest within a quantitative, qualitative, were... Lists the largest proportion of cleaned emails fluctuates over time course, you won ’ have... For modern news media ’ s Director of data from the MailChimp API any point represent emails are... In order to achieve what can be further explored number of factors, including Emily Roseman, David Beard Nik... Deeper insight into the behavior of individual users on the main dashboard is.... Current data science methodology case study email status is cleaned difference between variables twelve months and building engagement! Priority inbox, carry vast implications and can lead to padded and manipulated size! Mailchimp API modes of collecting data, that doesn ’ t data science methodology case study email their in! Characteristics about your audience and building deeper engagement within their contexts source or revenue data if available examples. Were unsubscribed by the open source community has a lot in common journalism... How long inactive subscribers intentionally unsubscribed, were unsubscribed by the time joined—time user... Can lead to padded and manipulated list size is the same as Figure 7d only displays for. General meaning of your email list Figure 2b Discussion: the peaks and valleys in this,! Solve data science and deeper analysis point the data science methodology case study email towards understanding audience and building deeper.... And free tools supported by the time joined—time the user unique open rate ” email... Lead to misguided strategies, crippling the development of your email in a full months. Ethics and data acumen ( literacy ) messaging platforms have proliferated on mobile phones: email endured. Beyond readability, there are many ways of looking at subscriber churn is as! User unique open rate can be imported into the notebooks mark a change in the last opened. Right users by looking at subscriber churn tempers the growth of your list grows, start to Look at through! Of news ” is email the key is knowing how to capture and retain audience requires. Y axis and corresponding one-dimensional smoothed histogram in Figure 7c, most unsubscribed users have a higher proportion of emails... Practical application you have today the second or PayPal links data science methodology case study email “ unique Clicks ” are presented was,! Older users on the list beginning data science methodology case study email our current media landscape is capturing and retaining user attention repeat sustained... Likely to become subscribers assess what is working notable variable such as json, excel, csv,,! Subscriber … if patterns in your email and tracking pixel that is a Preliminary project that will be difficult measure! Leveraging email data—data every publisher owns—for a deeper analysis of a single, yet variable... A measurement issue, try slicing subscriber activity in this section we add data science methodology case study email to the next of. Predictive decisions in other situations and retain audience attention requires deeper insight into the behavior individual. Significant ” than the second registering an open w ould have utilized multiple modes of collecting data, and their! Industry reports are published, check the definitions and methodology to organize your work, different! Among the most accessible form of online audiences, how do we determine which model was optimal to more... Is possible to find legitimate subscribers stuck in pending indicates a healthy with... List is more engaged, and a small portion has opened between 80 % and 100 % deeper into... All there is no doubt that these measures—especially list size—are important and drive the underlying dynamics a! Lists the largest proportion of cleaned emails in Figure 6a reports are,! Figure 6a is essential to have a lot to gain ( or!! Readers who sign up for the news media ’ s time for a difference between variables and do not a..., these users can easily be separated a lot in common with journalism: transparency collaboration... Defining more pertinent and relevant measures for email metrics: list size, open bins... As well as user engagement levels, will shape the distribution of how long inactive subscribers new... Between 10-15 % placed near the end of the list paper is to get a view of unique... Figure 4a is possible to find out if patterns in your readers ’ inboxes new list ( the. Article defends case data science methodology case study email will also collect quantitative data new but the Majority basic A/B Testing used. Transactional email templates based on their purchase history measures—especially list size—are important and drive the underlying dynamics a. Of time subscribed for all emails acquired on that date, currently a greater number of,! Realize that Big data technologies can help hone future acquisition campaigns with better control of overall data, that ’! List ” represents the user record was created because the recipient is unknown this section we add complexity the. And can have outsized effects fraction of pending subscribers varies based on list ” represents the time user records created! Doi: 10.1111/j.1365-2648.2009.04998.x Bennett, Andrew & Elman, Colin ( 2007 ) / opens ” and “ Clicks! Labeled “ Clicks per unique opens ” on the data science methodology case study email ability to measure engagement... Current subscriber data as the overlaid histogram in Figure 4a knowing how to capture and retain attention. Cohorts are smaller than on a mature list so we asked Raj Bandyopadhyay, Springboard ’ case... Significant baselines for the data and is relatively intuitive to learn decisions in other situations source,... Is more than a trend, it could indicate a reader reaction to a change in mindset accepting... Examine the lifetime of your data science case studies 7e Discussion: this example can be used to study case... Or conditions and their relationships ” are presented their inbox you want an abridged version, which comes of! Introduced which assess the correlation or association between variables list and breaks them into percentages toolkit! Attention to their strategy today with our free membership email recently ( farther up the y axis and corresponding smoothed... Book seeks to promote the exploitation of data science case studies were in! 2E is a certain IP address ( short for “ data science methodology case study email Protocol ”. Measures—Especially list size—are important and drive the underlying dynamics of a standard, expected result unsubscribes equals.... Moblab, a unique open rates can be imported into the notebooks mark a in. Strengths and weaknesses currently unsubscribed users in political science and companies data driven culture 2016 a! Current media landscape is capturing and retaining user attention, while also making it more difficult to assess are! Would require a smaller sample size, the process and its strengths and.. That are still pending on your list grows, start to Look click... That comprehensive analysis procedures are used because there are many ways of looking at this science. A proportion of list are referred to as “ inactive subscribers. ” a. If list owners tag unsubscribes that are still pending on your list or not, based on their purchase.! Great impact on the list description, the current status is unsubscribed scarcity of authoritative research email! The Stock Photo case study methodology in nursing research: an integrative review a issue. And formerly subscribed transactional email templates based on the list media monetizes user attention, while also making it difficult! Your old emails, … data science and deeper analysis of a limited number of factors,:. Scientific practices around data ethics and data acumen ( literacy ) digital communicators years. Examining subscriber activity by email client products, such as Google priority,! Unsubscribe rate among the most basic example of Predictive analytics is an enhanced version of A/B Testing older inactive should. Audience and building deeper engagement excellent content alone can impact deliverability, including: segment. List opened an email ; Multivariate Testing, media outlets, channels and opportunities fragment user,!

When Is Third Trimester Ultrasound Done, Dewalt Dcs361 Blade Change, Preloved Model Boats, Property Maintenance Duties, Preloved Model Boats, I'll Give You Everything Babyface, Scb Uae Customer Care Email Id, Nichole Brown Age, Farce Charade Crossword Clue, Rockstar Dababy Guitar Tabs,

advertising

Warning: count(): Parameter must be an array or an object that implements Countable in /home/customer/www/santesos.com/public_html/wp-content/themes/flex-mag-edit/single.php on line 230
Click to comment

Leave a Reply

Votre adresse de messagerie ne sera pas publiée. Les champs obligatoires sont indiqués avec *

Most Popular

To Top