Is content marketing a priority for you this year? Not sure where to really start when it comes to building a content marketing strategy? Join our content strategist who talks through the initial steps you need to take when planning a content marketing strategy and why personas are so important.
We take a look at:
- What personas are and why you should use them
- Finding out who your personas are and how to write them
- How personas benefit the success of your content marketing campaign.
Fact Store at Scale for Netflix Recommendations with Nitin Sharma and Kedar S...Databricks
As a data driven company, we use Machine Learning algos and A/B tests to drive all of the content recommendations for our members. To improve the quality of our personalized recommendations, we try an idea offline using historical data. Ideas that improve our offline metrics are then pushed as A/B tests which are measured through statistically significant improvements in core metrics such as member engagement, satisfaction, and retention.The heart of such offline analyses are historical facts data that are used to generate features required by the machine learning model. For example, viewing history of a member, videos in mylist etc.
Building a fact store at an ever evolving Netflix scale is non trivial. Ensuring we capture enough fact data to cover all stratification needs of various experiments and guarantee that the data we serve is temporally accurate is an important requirement. In this talk, we will present the key requirements, evolution of our fact store design, its implementation, the scale and our learnings.
We will also take a deep dive into fact vs feature logging, design tradeoffs, infrastructure performance, reliability and query API for the store. We use Spark and Scala extensively and variety of compression techniques to store/retrieve data efficiently.
Interactive Recommender Systems with Netflix and SpotifyChris Johnson
Interactive recommender systems enable the user to steer the received recommendations in the desired direction through explicit interaction with the system. In the larger ecosystem of recommender systems used on a website, it is positioned between a lean-back recommendation experience and an active search for a specific piece of content. Besides this aspect, we will discuss several parts that are especially important for interactive recommender systems, including the following: design of the user interface and its tight integration with the algorithm in the back-end; computational efficiency of the recommender algorithm; as well as choosing the right balance between exploiting the feedback from the user as to provide relevant recommendations, and enabling the user to explore the catalog and steer the recommendations in the desired direction.
In particular, we will explore the field of interactive video and music recommendations and their application at Netflix and Spotify. We outline some of the user-experiences built, and discuss the approaches followed to tackle the various aspects of interactive recommendations. We present our insights from user studies and A/B tests.
The tutorial targets researchers and practitioners in the field of recommender systems, and will give the participants a unique opportunity to learn about the various aspects of interactive recommender systems in the video and music domain. The tutorial assumes familiarity with the common methods of recommender systems.
Overview of the Recommender system or recommendation system. RFM Concepts in brief. Collaborative Filtering in Item and User based. Content-based Recommendation also described.Product Association Recommender System. Stereotype Recommendation described with advantage and limitations.Customer Lifetime. Recommender System Analysis and Solving Cycle.
Is content marketing a priority for you this year? Not sure where to really start when it comes to building a content marketing strategy? Join our content strategist who talks through the initial steps you need to take when planning a content marketing strategy and why personas are so important.
We take a look at:
- What personas are and why you should use them
- Finding out who your personas are and how to write them
- How personas benefit the success of your content marketing campaign.
Fact Store at Scale for Netflix Recommendations with Nitin Sharma and Kedar S...Databricks
As a data driven company, we use Machine Learning algos and A/B tests to drive all of the content recommendations for our members. To improve the quality of our personalized recommendations, we try an idea offline using historical data. Ideas that improve our offline metrics are then pushed as A/B tests which are measured through statistically significant improvements in core metrics such as member engagement, satisfaction, and retention.The heart of such offline analyses are historical facts data that are used to generate features required by the machine learning model. For example, viewing history of a member, videos in mylist etc.
Building a fact store at an ever evolving Netflix scale is non trivial. Ensuring we capture enough fact data to cover all stratification needs of various experiments and guarantee that the data we serve is temporally accurate is an important requirement. In this talk, we will present the key requirements, evolution of our fact store design, its implementation, the scale and our learnings.
We will also take a deep dive into fact vs feature logging, design tradeoffs, infrastructure performance, reliability and query API for the store. We use Spark and Scala extensively and variety of compression techniques to store/retrieve data efficiently.
Interactive Recommender Systems with Netflix and SpotifyChris Johnson
Interactive recommender systems enable the user to steer the received recommendations in the desired direction through explicit interaction with the system. In the larger ecosystem of recommender systems used on a website, it is positioned between a lean-back recommendation experience and an active search for a specific piece of content. Besides this aspect, we will discuss several parts that are especially important for interactive recommender systems, including the following: design of the user interface and its tight integration with the algorithm in the back-end; computational efficiency of the recommender algorithm; as well as choosing the right balance between exploiting the feedback from the user as to provide relevant recommendations, and enabling the user to explore the catalog and steer the recommendations in the desired direction.
In particular, we will explore the field of interactive video and music recommendations and their application at Netflix and Spotify. We outline some of the user-experiences built, and discuss the approaches followed to tackle the various aspects of interactive recommendations. We present our insights from user studies and A/B tests.
The tutorial targets researchers and practitioners in the field of recommender systems, and will give the participants a unique opportunity to learn about the various aspects of interactive recommender systems in the video and music domain. The tutorial assumes familiarity with the common methods of recommender systems.
Overview of the Recommender system or recommendation system. RFM Concepts in brief. Collaborative Filtering in Item and User based. Content-based Recommendation also described.Product Association Recommender System. Stereotype Recommendation described with advantage and limitations.Customer Lifetime. Recommender System Analysis and Solving Cycle.
PUC - Rio | Pontifícia Universidade Católica do Rio de Janeiro
Pós-graduação em Ergodesign de Interfaces: Usabilidade e Arquitetura de Informação
Professor: Edson Rufino
Aluna: Fernanda Sarmento
Avaliação Heurística
A avaliação heurística (Nielsen e Molich, 1990; Nielsen 1994) é um método para encontrar possíveis problemas de usabilidade em uma interface que consiste em recrutar um conjunto de avaliadores que examinarão a interface e avaliarão a sua conformidade com princípios de usabilidade já reconhecidos (chamados de "heurística").
Vantagens do uso do método: Feedback rápido e barato quando comparado a um teste de usabilidade; é possível executá-lo bem no início do processo de design, pode ser usado em conjunto com outras técnicas.
Desvantagens: Demanda conhecimento/experiência para aplicar as heurísticas de forma eficaz, portanto, pode ser difícil encontrar profissionais qualificados, a avaliação pode acabar identificando apenas problemas “menores”.
Redigido a partir de:
https://www.nngroup.com/articles/how-to-conduct-a-heuristic-evaluation/ + http://www.usability.gov/how-to-and-tools/methods/heuristic-evaluation.html
Optimizing your WeChat strategy through Data & Analytics55 | fifty-five
Are you using your data efficiently?
Do you want to go beyond standard WeChat KPIs like reach and fan acquisition, and start measuring engagement and conversion?
Do you want to start optimizing your WeChat performance and start driving business results more effectively?
Are you curious about WeChat analytics, both in terms of tools and applications?
Are you looking for a one-stop solution to auditing your Wechat performance and getting an actionable strategy for optimization?
fifty-five & Madjor uncover how data can be interpreted to help inform, audit and optimize your WeChat strategy.
우리는 지금 무엇을 하고있는지를 고민하나요? 아니면 무엇이 되어가고 있는지를 고민하나요? 네 맞습니다. 우리는 매년 무엇을 할지 고민합니다. 그런데 중요한것은 방향 즉 어디를 가고 있는지 입니다.
그래서 넷플릭스의 추천 시스템이 어디를 향해 가고 있는지를 살펴보고 추천시스템의 향해 가야할 Goal에 대하여 같이 이야기를 해보고자 합니다
Aula para a disciplina Produção e Ferramentas Colaborativas
Pós-Graduação em Engenharia de Software Centrada em Métodos Ágeis
Prof. Marcello de Campos Cardoso
www.mcardoso.com.br
Julho 2011
Interação e relacionamento PO com equipe de UX e Designers do Instituto de Pe...Alessandra Rosa
Os times que rodam Scrum tendem a ser auto gerenciáveis, nas tomadas de decisões e no andamento do projeto, ao introduzir o Time de Designers dentro do Scrum tivemos problemas de entregas e escopos. Após várias tentativas, o Time de Design começou a se planejar antes do time de desenvolvimento, funcionando bem até que os Designers começassem a participar das Soluções e propostas de UX - em parceria com o Product Owner dos projetos. Os conhecimentos dos Designers e a sua compreensão dos usuários com a tecnologia é fundamental para empresas de TI, este estudo analisa a parceria entre POs, Desenvolvedores e Designers para criar e desenvolver produtos que correlacionem o pensamento analíticos dos desenvolvedores com o pensamento sistêmico dos designers em times multi-disciplinares.
PUC - Rio | Pontifícia Universidade Católica do Rio de Janeiro
Pós-graduação em Ergodesign de Interfaces: Usabilidade e Arquitetura de Informação
Professor: Edson Rufino
Aluna: Fernanda Sarmento
Avaliação Heurística
A avaliação heurística (Nielsen e Molich, 1990; Nielsen 1994) é um método para encontrar possíveis problemas de usabilidade em uma interface que consiste em recrutar um conjunto de avaliadores que examinarão a interface e avaliarão a sua conformidade com princípios de usabilidade já reconhecidos (chamados de "heurística").
Vantagens do uso do método: Feedback rápido e barato quando comparado a um teste de usabilidade; é possível executá-lo bem no início do processo de design, pode ser usado em conjunto com outras técnicas.
Desvantagens: Demanda conhecimento/experiência para aplicar as heurísticas de forma eficaz, portanto, pode ser difícil encontrar profissionais qualificados, a avaliação pode acabar identificando apenas problemas “menores”.
Redigido a partir de:
https://www.nngroup.com/articles/how-to-conduct-a-heuristic-evaluation/ + http://www.usability.gov/how-to-and-tools/methods/heuristic-evaluation.html
Optimizing your WeChat strategy through Data & Analytics55 | fifty-five
Are you using your data efficiently?
Do you want to go beyond standard WeChat KPIs like reach and fan acquisition, and start measuring engagement and conversion?
Do you want to start optimizing your WeChat performance and start driving business results more effectively?
Are you curious about WeChat analytics, both in terms of tools and applications?
Are you looking for a one-stop solution to auditing your Wechat performance and getting an actionable strategy for optimization?
fifty-five & Madjor uncover how data can be interpreted to help inform, audit and optimize your WeChat strategy.
우리는 지금 무엇을 하고있는지를 고민하나요? 아니면 무엇이 되어가고 있는지를 고민하나요? 네 맞습니다. 우리는 매년 무엇을 할지 고민합니다. 그런데 중요한것은 방향 즉 어디를 가고 있는지 입니다.
그래서 넷플릭스의 추천 시스템이 어디를 향해 가고 있는지를 살펴보고 추천시스템의 향해 가야할 Goal에 대하여 같이 이야기를 해보고자 합니다
Aula para a disciplina Produção e Ferramentas Colaborativas
Pós-Graduação em Engenharia de Software Centrada em Métodos Ágeis
Prof. Marcello de Campos Cardoso
www.mcardoso.com.br
Julho 2011
Interação e relacionamento PO com equipe de UX e Designers do Instituto de Pe...Alessandra Rosa
Os times que rodam Scrum tendem a ser auto gerenciáveis, nas tomadas de decisões e no andamento do projeto, ao introduzir o Time de Designers dentro do Scrum tivemos problemas de entregas e escopos. Após várias tentativas, o Time de Design começou a se planejar antes do time de desenvolvimento, funcionando bem até que os Designers começassem a participar das Soluções e propostas de UX - em parceria com o Product Owner dos projetos. Os conhecimentos dos Designers e a sua compreensão dos usuários com a tecnologia é fundamental para empresas de TI, este estudo analisa a parceria entre POs, Desenvolvedores e Designers para criar e desenvolver produtos que correlacionem o pensamento analíticos dos desenvolvedores com o pensamento sistêmico dos designers em times multi-disciplinares.
Prezentacja (z notkami) przygotowana na webinar, który miał miejsce 10 kwietnia 2018 roku.
Nagranie video z webinaru dostępne jest na Youtube: https://youtu.be/OjX_jmE2foI
Po więcej informacji o nowych wydarzeniach i webinarach zapraszam na Facebook: https://facebook.com/wojtekkutylaux
Wprowadzenie do EVO Tom'a Gilb'a dla Agile WarsawMichał Parkoła
Tom Gilb od dziesięcioleci rozwija i pomaga stosować metodykę EVO, z której garściami czerpały podejścia, które dzisiaj nazywamy Agile.
Zobacz o czym zapomniał Jeff Sutherland i spółka gdy kopiowali EVO.
Coraz więcej firm decyduje się na wdrożenie oprogramowania, które podniesie efektywność pracowników. Dobrze zrealizowana inwestycja daje bowiem korzyści nie tylko finansowe. Zakup nawet najlepszego oprogramowania nie gwarantuje jednak efektów, jeśli wdrożenie nie zostanie odpowiednio przeprowadzone.
Więcej na ideo.pl
Jak przekonać użytkowników do zmiany zachowania? Projektowanie perswazyjneSymetria
Korzystanie z publicznej toalety nie zawsze należy do najprzyjemniejszych czynności. Często można zaobserwować, że poprzednicy mieli spore trudności z celnością. Czy projektanci mogą temu przeciwdziałać? Czy mogą zaprojektować takie rozwiązanie, które poprawi celność i tym samym przyczyni się do zmniejszenia kosztów utrzymania porządku? Okazuje się, że tak. Odpowiedzią na to wyzwanie jest projektowanie perswazyjne.
Przeczytaj więcej na: http://symetria.pl/blog/artykuly/projektowanie-perswazyjne/
Pierwszy krok w projektowaniu aplikacji mobilnej nie wymaga żadnych umiejętności technicznych. Mimo to, jest on zdecydowanie najtrudniejszy. Jest nim wypracowanie odpowiedniego pomysłu na samą aplikację. Jak więc zaprojektować aplikację mobilną, tak aby użytkownicy ją pokochali?
Przeczytaj więcej na: http://symetria.pl/blog/artykuly/ux-aplikacji-mobilnej/
Prototypowanie użytkowników czyli persony w projektowaniu interfejsów użytkow...Symetria
Czas to pieniądz, a każde narzędzie stosowane w trakcie projektowania interfejsów to nie tylko czas, ale i wyzwanie, dodatkowy wysiłek. Spróbujmy zastanowić się, w jakich sytuacjach i w jaki sposób wykorzystać znane od lat, choć stosunkowo rzadko stosowane narzędzie w postaci person.
Dla laureata konkursu – Miltaria.pl, zrealizowany został pakiet darmowych usług o wartości 50 000 złotych. Wykonano badania użyteczności, analizę dobrych praktyk, projekt funkcjonalny, a także kreacje reklamowe.
Dzięki opowieściom przypominamy sobie dzieciństwo – magiczne miejsce, gdzie każdy wraca z sentymentem. To właśnie emocje sprawiają, że ciekawe historie chętnie i długo przechowujemy w pamięci. Właściwości te można wykorzystać we współczesnym marketingu. Choć każda marka ma swoją historię, sztuka polega na tym, aby ją umiejętnie opowiedzieć.
Dzisiaj każdy z nas jest częścią jakiejś społeczności. Chcemy dzielić się z innymi swoją pasją, ciekawostkami znalezionymi w sieci czy zdjęciami z rodzinnych uroczystości. Z drugiej strony sami lubimy „podglądać” internetowe życie naszych znajomych, komentować je i w nim uczestniczyć. W sieci pozostawiamy mnóstwo informacji o sobie samych, czy więc możemy chronić do nich dostęp po prostu wyłączając komputer?
Wyszukać nie znaczy znaleźć – świadomość tego ryzyka powinna skłaniać do pracy również nad wyglądem i użytecznością stron wyników wyszukiwania. Prezentacja i artykuł przedstawiają aspekty, które należy wziąć pod uwagę projektując ten etap interakcji.
1. Miary użyteczności Na podstawie „Measuring the user experience” Tom Tullis, Bill Albert Natalia Bednarz 6.03.09
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7. Przedziały ufności – metoda Walda Przedziały ufności jako funkcja wielkości grupy respondentów. 6.03.09
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12. Lostness N – liczba różnych stron odwiedzonych S – całkowita liczba odwiedzonych stron R – optymalna liczba stron L=sqrt[(N/S – 1) 2 + (R/N – 1) 2 ] L<0,4 brak większych błędów L>0,5 obecność istotnych błędów 6.03.09