How to turn your content model into a powerful marketing and SEO weapon

Providing your website with a structured content model is not only the best solution to better organize your content, but also a powerful strategy to improve the SEO of your website and increase organic traffic.

In this article, we’ll explain how the WordLift entity-based model, coupled with the new feature WL Mappings, will allow you to add a more specific markup to your content and to obtain a Knowledge Graph capable of communicating to search engines in a more effective way.

Why is the content model becoming a key tool for SEO?

During his webinar on content modeling for SEO in the WordLift Academy, Cruce Saunders highlights some of the main features that make the content model an indispensable tool for managing and enhancing online content.

In fact, the content model:

  • Specifies how information is organized on your website
  • Makes content more visible to search engines
  • Allows you to reuse content through different channels

Structured content model, in short, not only allows you to better organize data and information but to do it within a malleable structure capable of communicating:

  • to search engines through the use of structured data
  • to users through the enhancement of the user experience and the possibility of reusing the content by presenting it in the form of different layouts both on the site and in the SERP to respond to specific search intents (the same article, for example, may appear in the form of a snippet, of blue link, promotion, etc.)

Structuring your content model means creating a three-dimensional identity capable of highlighting your content and the relationships underlying it. This allows search engines to recognize you among hundreds of pieces of information, making you more visible to users who correspond to the search intent related to your business.

The more the content model is rich in structured data, the more chances you’ll have to meet exactly the users interested in you. That’s why we created WordLift Mappings, a new feature that allows you to select the information and connections that are truly relevant for your business and to create an increasingly specific and refined Knowledge Graph to highlight only the most relevant facets that make your identity more authoritative. 

Through our entity-based model and WordLift Mappings, your content model becomes a powerful SEO weapon and a valuable resource to increase the value of your online data.

WordLift Mappings helps you create a custom Knowledge Graph and increase your online authority

WordLift creates a personalized and highly performing Knowledge Graph through the markup and the creation of a customized entity-based vocabulary containing the most relevant data to help Google better understand your online content.

Remember that Google uses entities to satisfy users’ search intent and allow them to find the best results. For this reason, an increasingly refined entity-based model such as WordLift is key to increase the visibility of your content for search engines.

WordLift Mappings increases the accuracy of this process and allows you to take greater care of your content and your Knowledge Graph.

Advanced Custom Field for how the new WordLift extension works

By connecting to ACF (Advanced Custom Field), a WordPress plugin that allows you to create advanced fields to specify the attributes that characterize your content, WordLift Mappings allows you to structure your data starting from the fields that you have already configured with ACF or from new fields based on the taxonomy.

This means having more and more structured content, which can be used to add relevant details to your Knowledge Graph and shaped in different configurations to improve the user experience.

In this webinarAndrea Volpini and Jason Barnard explain how they used WordLift Mappings to improve Jason’s content model and Knowledge Graph. Jason shows how he obtains a Knowledge Graph in which only the most relevant data to create an authoritarian and coherent Brand SERP are structured to stand out in the search results.

With over 100 podcasts made in collaboration with some of the greatest SEO experts on the planet, Kalicube – Jason Barnard‘s website – has an enviable wealth of content, relevant to the entire digital marketing sector. Thanks to WordLift Mappings, we helped Jason structure this content by following a model that focuses on content, events and people. Thus, each guest of Jason’s podcast has his own page connected with the podcasts in which he participated and with the events in which the podcasts were recorded.

In this way, the architecture of the Knowledge Graph is customized on the basis of the content model and the “network” of the links between the contents becomes the bearer of meanings and allows you to predict further connections. Below you can see the entity-based content model applied to Kalicube through WordLift Mappings.

What can you realistically expect in terms of traffic? How long does it take?

In recent weeks, our SEO team has implemented a new content model on the site of an American customer who deals with the dismantling and re-evaluation of used hardware on a large scale.

The results? After the first week, traffic increased by 14.6% and the growth curve does not seem to stop. To analyze the impact, isolating other factors that may influence the SEO of the site, we have developed a predictive model based on Bayesian networks which, analyzing the traffic in the month preceding the introduction of the WordLift Mappings, allowed us to isolate the benefit to the net of other ranking factors (it’s called causal inference analysis).

Want to find out how to analyze your traffic data to optimize SEO?

Contact our experts!

Here we see the real clicks in black and the traffic we would have had in blue (that is, the traffic predicted by the mathematical model), then in the following chart the difference between the real traffic and the estimated traffic and finally the delta of increase. In this way, we can be sure that, as analyzed, it has statistical relevance and is related to the introduction of the new content model. ?

Data source: Google Search Console

In summary, WordLift Mappings allows you to:

  • Build a Custom Knowledge Graph based on your content model
  • Improve the SEO of your website through structured data
  • Shape the structure of your content to improve the user experience
  • Reuse chunks of content through different configurations to respond to different research purposes
  • Enhance any type of content composed of reusable elements (articles, courses, events, How-Tos etc.)

The implementation of a custom Knowledge Graph through WordLift Mappings has a positive and measurable impact on traffic.


The Role of Content Structuring in Voice Search and Beyond

In 1996 Bill Gates wrote “Content is King”, predicting a world where content would have been the main wealth on the Internet. Although this prediction has been a catchphrase in the contest of digital marketing in the 2000s, nowadays it could sound a little naive. It isn’t, if you rethink content separating it from its containers and try to understand and follow its law

Don’t think in terms of pages, think in terms of entities

Pages are just one of a thousand ways in which content can be rendered and displayed to your users. An entity is the real single brick of your content strategy. It can be displayed through a page, but it’s something more. It is a thing (or a person, a place, an event, etc.) that has its own properties and relationships with other things. 

Adding markup to your content you can define and describe your entities and help search engines better understand your content. Let’s say for example you have a recipe: as an entity, this recipe will have many properties such as recipeCuisine, recipeIngredient, recipeInstructions, recipeYield… and a lot more. All these properties can connect the entity to other entities or just exist as single data points. 

On the left side, you see a recipe on IINH, as users would see it on the web page, while on the right side, you have the same recipe as Google sees it through structured data.

Let’s say I’m looking for an apple pie with one single egg — because I have just one in the fridge, semantic search engines could give me the right recipe thanks to the additional information related to the entity. So, in the end, entities allow you to give a better answer to your potential readers

The same recipe presented on Google’s SERP in the recipe carousel

Why are entities relevant in this context?

Structured content can help you build Actions for the Google Assistant upon some entity types such as recipes, how-tos, news articles and podcasts. And here is how markup comes handy for voice search

Moving from building pages to creating structured data helps us create relationships between entities that matter. Entities are not isolated items, they are all connected into a cluster which is semantically meaningful.

This means that through entities you can feature different angles of a complex thing. 

For example connecting all information related to a course or a webinar across multiple pages can be strategic to stand out on Google search and is the best way to answer to different user intents. 

Related articles

How to turn your content model into a powerful marketing and SEO weaponSERP Analysis with the help of AIHow To Build A High-Converting Video Website That RanksDoes structured data create a competitive advantage in SEO?

Structure your content building your own content model — and stick with that

As I said before, entities are just the first brick of your content strategy. Content modeling is the law that underlies your content. Structuring the content of your website allows you to reuse it in different formats and match different search intents. 

For example, the content model of the WordLift Academy allows us to repurpose our content in different formats. Each main content is a webinar which is connected to different data points such as creation date and duration, other entities such as the topics covered during the webinar and the main speaker, and media such as the cover image, the profile picture of the speaker, and the video recording. 

The Entity-based content model of the WordLift Academy

All this information can answer to different search intents and function as different entry points to the main content. 

Experiment new formats starting from your content wealth  ?

Now, let me tell you a story. 

Recently, we’ve joined Google’s Mini Apps Early Access Pilot. The idea was to offer to the user an app experience built into the SERP to navigate into the Academy content. 

I won’t enter into the details of the technological stack used to create this Mini App prototype through Google’s console. What matters here is that, having a structured content we have refined the search for WordLift courses allowing the users to navigate through them by selecting one or more topics of interest and/or a speaker. 

A preview of the WordLift Mini App and some query examples

As the pilot has been shut down due to COVID-19, you won’t see it on the SERP anytime soon. ? But… we are planning the same structure — well, with a few changes in terms of technology – to build an Assistant App for Google. ?

So users will be able, for example, to look for all the webinars about SEO by Jason Barnard on our Academy just invoking the App.  

What’s the take-away of this story? 

Formats may change and evolve, experiments come and go… but a strong content model allows you to reuse your content in different environments.


È viva la lezione di Modigliani


Il primato della lotta alla disoccupazione contro il monetarismo dominante. Cento anni fa nasceva l’economista premio Nobel, costretto all’esilio dalle leggi razziali di Mussolini

Franco Modigliani (a sinistra, 1918-2003) mentre riceve il premio Nobel per l’economia, che gli fu assegnato nel 1985,  dalle mani del re Carlo XVI Gustavo di Svezia (foto Ansa)

Franco Modigliani (a sinistra, 1918-2003) mentre riceve il premio Nobel per l’economia, che gli fu assegnato nel 1985, dalle mani del re Carlo XVI Gustavo di Svezia (foto Ansa)shadow

Franco Modigliani — uno dei maggiori economisti della seconda metà del Novecento, premio Nobel per l’Economia nel 1985 — era nato un secolo fa, il 17 giugno 1918. Aveva perciò venti anni nel 1938 e stava per laurearsi in legge a Roma quando vennero promulgate le leggi razziali. Il consiglio di Bruno Calabi, padre della sua futura moglie e proprietario delle Messaggerie Italiane, che vennero in quella circostanza cedute alla Mondadori, fu di lasciare subito e definitivamente l’Italia. Franco e Serena si trasferirono a Parigi, si sposarono e nell’agosto del 1939 si imbarcarono a Le Havre sul Normandie — uno degli ultimi piroscafi a traversare l’Atlantico prima dello scoppio della guerra; giunsero a New York il 28 agosto, quattro giorni prima dell’invasione della Polonia.

Franco Modigliani (1918-2003): docente al Mit di Boston, fu anche firma del «Corriere della Sera»
Franco Modigliani (1918-2003): docente al Mit di Boston, fu anche firma del «Corriere della Sera»

Per sopravvivere Modigliani trovò lavoro come venditore di libri importati dall’Italia. Contemporaneamente, grazie a una borsa di studio di Max Ascoli, un antifascista italiano emigrato da tempo negli Stati Uniti, si iscrisse ai corsi serali di economia della New School for Social Research. Negli anni Venti, la New School era stata un’oscura Università per l’educazione degli adulti creata da un miliardario filantropo, ma negli anni Trenta, sotto la protezione di Franklin Delano Roosevelt e soprattutto della moglie Eleanor, divenne uno dei grandi centri universitari che accoglievano docenti e studenti in fuga dall’Europa, tanto da essere soprannominata l’Università in esilio. In quel periodo alla New School Modigliani ebbe due maestri: Jacob Marschak, un economista matematico russo che dopo la rivoluzione di Ottobre si era rifugiato in Germania da dove era dovuto fuggire all’avvento del nazismo, e Abba Lerner, anche lui ebreo, inglese, che aveva fatto i primi passi alla London School of Economics con Friedrich von Hayek, ma si era convertito alle idee di John Maynard Keynes dopo la pubblicazione nel 1936 della Teoria generale dell’occupazione, dell’interesse e della moneta.

La coincidenza fortunata per Modigliani fu che i suoi anni di apprendistato economico coincisero con «la rivoluzione keynesiana», cioè con la trasformazione radicale dell’impostazione degli studi economici seguita alla pubblicazione nel 1936 del libro di Keynes. La Teoria generale — scrisse Paul Samuelson qualche anno dopo — «colpì la maggior parte degli economisti sotto i trentacinque anni con la virulenza inaspettata di una malattia che attacchi per la prima volta e decimi una tribù isolata dei Mari del Sud». Essa, in effetti, segnò in modo indelebile Modigliani e gli economisti della sua generazione: «Keynes — scrisse Modigliani nella sua autobiografia Avventure di un economista (Laterza) — ci dava la speranza che la malattia misteriosa che aveva originato la tremenda recessione del 1929 fosse qualcosa che poteva essere compresa… Quegli studi ci infiammavano. Capimmo di essere su una linea di frontiera… stavamo combattendo una guerra importante per il futuro». Keynes per l’economia e Roosevelt per la politica sono stati la duplice ispirazione cui Modigliani è rimasto fedele per tutta la vita.

Il ciclo vitale del risparmio

Nel gennaio del 1944 apparve su «Econometrica», una delle più importanti riviste americane di economia, un articolo di Modigliani, che aveva solo 24 anni, intitolato Liquidity Preference and the Theory of Interest and Money. L’articolo conteneva una fra le prime, se non la prima, formulazione matematica completa della Teoria generale. Modigliani sosteneva che la rigidità dei salari, e cioè il fatto che il salario monetario non si riduca in presenza di disoccupazione, spiega perché i sistemi di mercato non realizzano automaticamente la piena occupazione. Forse, con il senno del poi, si può sostenere che l’articolo contenesse un fraintendimento della Teoria generale, le cui conclusioni non richiedono questa ipotesi sulla rigidità dei salari. Ma l’articolo comunque rafforzava gli argomenti sulla necessità di una politica economica attiva per realizzare e mantenere la piena occupazione.

Oltre a mettere in dubbio le vecchie certezze sulle virtù del mercato, la Teoria generale aperse di colpo nuove promettenti aree di ricerca. Una di queste fu lo studio delle determinanti del risparmio nel breve e nel lungo periodo. Keynes aveva sostenuto che, al crescere del reddito, il consumo tende a crescere, ma non quanto il reddito. Dunque anche il risparmio cresce al crescere del reddito. Ma che cosa determina esattamente la propensione al consumo e al risparmio? Modigliani avanzò l’ipotesi che la propensione al risparmio muti nel corso della vita secondo un ciclo che essenzialmente vede le persone risparmiare da giovani e spendere da vecchie il risparmio accumulato. Su questa ipotesi continuò a lavorare a lungo traendone implicazioni importanti. Nel 1985 la Commissione del Nobel nelle motivazioni del premio si riferì soprattutto a questa filone di ricerca.



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L’unicità di un attore come Massimo Troisi

Il 5 marzo 1981 Massimo Troisi debutta al cinema in veste di regista-attore con Ricomincio da tre: il film incassa 15 miliardi di lire e viene proiettato per 43 settimane consecutive nelle sale, segnando un record ancora oggi imbattuto. Da quel giorno, l’artista napoletano ha conosciuto una lunga serie di successi, terminata solo con la morte prematura avvenuta durante  le riprese de Il Postino nel 1994. In tredici anni ha lavorato in dodici pellicole, di cui solo cinque nella veste di attore. Eppure, Troisi riuscì a cambiare le regole della comicità al cinema, plasmate da artisti come Manfredi, Sordi, Tognazzi e Villaggio Oggi la nostra comicità è orfana del lascito di Troisi, molto lontana da quella che l’attore aveva portato a teatro, in televisione e introdotto sul grande schermo.

La forza comica di Troisi si trovava soprattutto nella visione sarcastica e romanzata del quotidiano, dove ogni evento diventava spunto per un umorismo spontaneo, immediato, paradossale, mai volgare, aggressivo o urlato. Non aveva bisogno di forzare una situazione o di una parolaccia per strappare la risata del pubblico, ma si basava sulla mimica inconfondibile e un talento quasi istintivo per i tempi della battuta. Dal teatro-cabaret al cinema, dalla radio alla tv, la comicità italiana di oggi si nutre in molti casi  di urla sguaiate, volgarità, bassezze, qualunquismi e stereotipi. Anche per questo è sbagliato considerare Massimo Troisi uno dei maestri della comicità italiana. L’attore rappresenta più un unicum privo di eredi artistici. Venticinque anni dopo la sua morte non esiste una “scuola Troisi” e il suo ricordo sfocia nella citazione o nei peggiori dei casi nell’emulazione, mentre non viene scalfito quell’alone di irripetibilità che da sempre lo ha accompagnato in una vita segnata da una malformazione cardiaca scoperta all’età di 14 anni.

Il Postino, 1994.

Per capire l’unicità di Massimo Troisi possiamo partire dal linguaggio e prendere in prestito quanto detto da Roberto Benigni, con cui ha diretto nel 1984 il film Non ci resta che piangere. Nella poesia dedicata a Troisi dopo la sua morte, Benigni scrive: “Morto Troisi muore la segreta arte di quella dolce tarantella, ciò che Moravia disse del Poeta io lo ridico per un Pulcinella”. Parafrasando, l’arte di Troisi è Troisi, al punto che gli è stato riconosciuto lo status di “maschera” che prima era stato di Totò. Quando Ettore Scola nel 1990 gli affidò il ruolo di Pulcinella ne Il Viaggio di Capitan Fracassa, sembrò una naturale sovrapposizione.

Il concetto di maschera è ancor più evidente nei film di cui Troisi è stato regista o co-regista. I protagonisti sono una proiezione della sua personalità in diversi contesti: impacciati e timidi, vivono una condizione di esuli più che di emarginati, trovando la risata nell’incomprensione, nella parola smangiucchiata, nei gesti abbozzati del corpo. Lo si vede con Gaetano in Ricomincio da tre, il soggetto più autobiografico nella carriera di Troisi, ma anche con Mario Ruoppolo ne Il Postino (co-diretto con Michael Radford), quando l’artista di San Giorgio a Cremano ha mostrato la sua indole più nostalgica, matura e intima, che gli valse la candidatura postuma per l’Oscar come miglior attore protagonista nel 1996.

Massimo Troisi non era solo divertente, ma tagliente. La sua carriera è stata una costante operazione di decostruzione della società, usando Napoli come suo luogo archetipico. Troisi ha offerto un’immagine della sua città ribaltando i luoghi comuni. Per riuscirci ha seguito due percorsi: nel primo ha rappresentato Napoli con lo sguardo esterno, mentre nel secondo l’ha raccontata come può fare solo uno dei suoi abitanti. Dagli inizi in calzamaglia con I Saraceni, poi diventati La Smorgia insieme a Enzo Decaro e Lello Arena, dai piccoli teatri al passaggio in tv nelle trasmissioni Non stop e Luna Park, fino al clamoroso successo da “solista” al cinema, Massimo Troisi ha tentato di spezzare tanto la visione conservatrice che hanno alcuni dei suoi abitanti su Napoli, quanto i pregiudizi del resto degli italiani.


Gérer les produits temporairement indisponibles sans perdre en référencement

La rupture de stock est une situation assez fréquente sur les sites ecommerce. Elle s’accompagne souvent de déception chez l’internaute et parfois de perte de CA. Voici comment gérer le cas des produits temporairement non disponibles (stock épuisé), sous l’angle SEO mais aussi expérience utilisateur.

Analyse de la situation
Le problème est-il temporaire ?

Je pense que la première question à se poser concerne la durée de cette indisponibilité. Essayez d’évaluer précisément combien de temps va durer la rupture de stock.

Si vous vous rendez compte que ça risque d’être très long, voire définitif, il faut mieux retirer le produit du catalogue. Dans ce cas, lisez comment gérer un produit définitivement supprimé.

Dans le cas contraire, passez en revue les solutions décrites ci-dessous, mais prévoyez vraiment quelque chose car ce cas de figure peut nuire à vos activités…

rupture de stock et référencement
Comment gérer la rupture de stock pour le référencement ?

Transformez un problème en opportunité !

En attendant de retrouver du stock pour votre produit, ayez en tête qu’il est possible d’en vendre d’autres en remplacement ou en complément. J’en reparle plus loin, mais votre principal objectif doit être d’éviter que l’internaute quitte votre site pour acheter son produit ailleurs.

Certes, le produit indisponible à la vente crée de la déception chez l’utilisateur. Mais tout va dépendre de votre façon de gérer cette problématique. Il faut rassurer l’internaute, lui faciliter l’achat ultérieur ou lui proposer une autre solution (produit de substitution).

? En complément, lisez aussi comment bien référencer une fiche produit.

Liste des solutions possibles

Mettre la fiche produit en 404 : mauvaise idée

Erreur 404

Il ne faut pas supprimer la page et renvoyer un code 404 car vous avez besoin de conserver le positionnement de la page dans les SERP. si vous la retirez, puis la remettez, plusieurs fois, alors Google ne va plus rien comprendre et il est probable que votre page perde son référencement.

Si besoin : rappel de tous les codes HTTP

Rediriger la fiche produit en 301 (redirection permanente)

C’est une mauvaise idée, comme la 404, car vous perdrez votre référencement.

Evidemment, si vous savez que le produit ne sera plus jamais vendu, pourquoi pas faire une redirection 301 vers la catégorie mère, ou vers un produit qui le remplace précisément.

Notez qu’il est possible également dans ce cas de faire une 404 (ou 410) personnalisée pour expliquer la situation à l’internaute et lui lister des produits équivalents.

Rediriger la fiche produit en 302 (redirection temporaire)

Ce n’est pas non plus une bonne idée, ou alors il faudrait vraiment :

  • que le produit soit à nouveau disponible sous quelques jours maxi (à mon avis). Si ça dure trop, Google va considérer qu’il s’agit d’une redirection permanente. Si ça dure pas longtemps, vous retirez la 302 mais dans combien de temps Google reviendra la crawler ?
  • et que l’internaute soit temporairement redirigé vers une page qui ne le déçoit pas (pas évident)

Préciser la situation dans les données structurées avec ItemAvailability

C’est une fausse bonne idée 😉 propose différentes valeurs qui peuvent aider à décrire la situation :

  • Discontinued
  • InStock
  • InStoreOnly
  • LimitedAvailability
  • OnlineOnly
  • OutOfStock
  • PreOrder
  • PreSale
  • SoldOut

Mais :

  • l’internaute qui verra dès les SERP que votre produit n’est pas en stock, n’aura sans doute pas envie de venir sur votre site
  • pour Google c’est également problématique car si ça dure pas longtemps, vous repassez à InStock mais dans combien de temps Google reviendra crawler la page ?

Proposer de récupérer le produit en magasin

stock épuisé

C’est déjà mieux : votre site ecommerce ne l’a pas en stock mais vous pouvez le vendre, à condition que le client aille le chercher dans le magasin près de chez lui. C’est juste la livraison à domicile qui n’est pas possible.

Si possible, gérez dans ce cas la liste des magasins possibles, et précisez si jamais celui initialement choisi par le client ne l’a pas non plus en stock.

Proposer la précommande

Si vous n’avez aucun doute sur le fait que le produit sera prochainement en stock, la meilleure solution est de proposer de précommander l’article. Montrez à l’internaute qu’il peut faire partie des premiers à acheter le produit dès son retour en stock !

Proposer de l’aide (service client)

Si vous n’avez pas de système de notification de future disponibilité, proposez au minimum que le service client entre en contact afin d’aider le client. C’est ce que fait :

Proposer de prévenir dès que le produit est disponible

Finalement, n’est-ce pas la meilleure solution en cas de rupture de stock ? Il faut que votre CMS gère cette fonctionnalité : l’affichage d’un texte du genre « Soyez le premier à être informé dès que ce produit est en stock » et un bouton « Prévenez-moi » (qui remplace « Ajouter au panier »).

Si possible, affichez aussi le délai de réapprovisionnement, ou mieux encore la date du retour en stock si vous la connaissez (« date de réassortiment »).

Evidemment, vous pouvez là aussi mettre en avant des produits de remplacement, ou d’autres conditionnements. Ceci est censé être gérer par votre système de cross selling : à vous de vérifier qu’il fonctionne bien.

Bonus : proposer une promotion

Que ce soit directement sur la fiche produit ou dans le mail de notification (quand le produit redevient disponible), vous pouvez offrir une réduction ! A vous de calculer selon votre marge sur le produit, mais c’est un très bon moyen de positiver une situation initialement décevante.

Autres conseils

Anticipez !

C’est évident, mais c’est mieux d’éviter la situation des produits hors stock, ou de la déception des internautes qui les consultent.

Une manière de limiter le problème, c’est de filtrer en amont pour ne pas afficher (par défaut) les produits hors stock. Voici l’exemple chez Amazon (cela dit, ce filtre ne semble pas toujours fonctionner, on peut trouver des articles sans stock même sans cocher la case) :

Même si ça ne change rien au problème, n’hésitez pas à indiquer quand un produit n’a presque plus de stock : ça peut déclencher des achats… C’est ce que fait par exemple Amazon :

Pensez au moteur de recherche interne !

Dans votre moteur de recherche interne, laissez l’utilisateur pouvoir filtrer pour exclure les produits hors stock, ou bien listez-les après les produits en stock.

Et vous, comment gérez-vous les produits hors stock ou indisponibles ?


Test article

We’re talking about WordLift here


Netflix, Case study of Digital Transformation.

Netflix 2.0 — Video Streaming

Since starting its video streaming services in 2007, Netflix has successfully grown its business. By the end of 2016, it had nearly 94 million members globally — expected to reach 100 million mark during the frst half of 2017. Netflix video streaming consumes 37% of downstream internet bandwidth during primetime hours in the USA — far ahead of YouTube, Amazon and Facebook.

Netflix has become the defacto primetime entertainment on the web. It can be streamed on computers, mobile phones, tablets, smart televisions and video game consoles.

Origins: DVD-by-Mail Business Model

The classic management textbook theories would have predicted that Netflix should have now failed. Indeed in January 2007, JP Morgan Scurities downgraded the Netflix stock citing high competition and most wondered how Netflix might create a ‘second act’ beyond DVD Distribution. After all, it started in 1997 as a mail-order DVD-by-Mail business with monthly subscription fees so that consumers could avoid late fees. During the first decade, it had built impressive logistics chain with over 50 regional warehouses to distribute the DVDs to its customers. By February 2007, it had distributed its billionth DVD. That success and that kind of growth should have trapped the company to define its business model with core competency in logistics and distribution.

But Netflix’s different in the sense that it had recognized the power of data and analytics. It had developed a superior recommendation engine, Cinematch to better predict the pattern of request of DVD titles by subscribers. It even organized open contest — Netflix Prize — to win $1 million prize to anyone who could improve on its algorithms. It was a data-driven company before data and analytics were in vogue.

By 2009, it had over 100,000 DVD titles and 10 million customers. It could have continued on its trajectory. But, it didn’t. Netflix innovation focused on two dimensions: logistics and analytics.

Blockbuster and other video rental physical stores didn’t recognize possible disruption from a mail-order subscription company like Netflix. Blockbuster even turned down an opportunity to acquire Netflix in 2000.

Netflix 1.0 was about disruption of physical stores.



Every year sees the birth of tens of thousands of new startups. This means it’s getting harder and harder to get some attention as a fledgling company. There simply aren’t enough journalists to give startup the attention they might deserve.

TNW started out as a prime source for news about startups over ten years ago, and we’d like to honor those roots by creating more room to feature exciting and interesting new startups. In partnership with our business intelligence service Index, we’re launching Startup Stories, a new series we’re kicking off today.

The format consists of four simple questions: What does it do, where did the founders get the idea, what does the business model look like, and finally a ‘random box’ for fun anecdotes, extra info, profanity or whatever a startup would like to share with our audience. 

The first company to be featured today is WordLift, a startup that makes online content easily understandable for chatbots, crawlers, and personal digital assistants like Siri or Cortana. Basically WordLift should be able to take this post, and parse it in a way that you can ask Siri ‘What is this new series Startup Stories on The Next Web?’ and Siri can give you an answer. But let Andrea Volpini, CEO of WordLift explain this in a far more eloquent way:

What does your startup do?

Wouldn’t it be great if you could talk with your favorite websites and blogs just like you do with your car or with Siri?

WordLift helps content writers work better, by letting them focus on writing great articles without worrying too much about how search engines work.

WordLift uses AI to grow organic traffic by translating articles into machine-friendly content that chatbots, search crawlers and personal digital assistants – like Google Assistant, Siri and Alexa – use to help consumers take actions.

The evolution of today’s search engines and the rapid adoption of personal assistants (PAs) – capable of understanding user intent and behaviors through available data – require an upgrade of the existing editorial workflow for bloggers, independent news providers and content marketers. With voice search coming on strong, websites now have to compete directly for business (and struggle to be on top of search results), by bringing targeted information at lower prices. With voice there are not many alternatives: Either you get featured on Google, or you get nothing.

In this context, data curation and metadata management become crucial tools to help bloggers and news publishers create the added value required to build a direct relationship with their readers.

WordLift targets smart content publishing focusing on automating SEO and bringing immediate economical value by increasing traffic and reducing the time spent on content curation and search marketing.

The processing is done in the cloud. WordLift analyzes articles and transforms text into metadata. Data is automatically published as five-stars linked open data and made available to machines. We also measure the performance of the content on Google in terms of search rankings and other factors that might influence organic traffic. This data is presented to the editors to help them improve their editorial plan and increase their reach.

Why did you come up with this idea?

Quite simply by looking at the structured knowledge available in today’s digital networks and how search engines were starting to take advantage of it. Try yourself asking Google who built the Colosseum and you will get an immediate answer that comes straight from Wikipedia. This information has been encoded in such a way that the Google Assistant can understand it.

We’ve built WordLift so that information is extracted from textual content and published in a user’s graph. This allows Google and others PAs to learn faster from blogs and websites.

Try it now, and ask Google Assistant “How old is Andrea Volpini?”

Large graphs like Freebase, DBpedia and Wikidata represent the majority of the information that computers use to interact with humans. There are also advanced linguistic resources, structured as linked data, that help computers understand human language (lexical databases like BabelNet or WordNet) and this is also an interesting area of development. But there is very little available in terms of tools that smaller bloggers can use to create their own structured knowledge.

We thought: Why don’t we create something that bloggers and editorial teams can use to build their own knowledge graphs? Why on Earth should a blogger deal with the bureaucracy and complexity of Wikipedia to share a fact he or she knows, or to add a new expression his or her tribe is using?

This is why WordLift was created. We went through several years in the making to create an easy-to-use annotation tool that could help anyone build his or her own knowledge graph and share a personal viewpoint with machines.

How do you make money?

WordLift is a Software-as-a-Service (SaaS). Bloggers and digital publishers pay a monthly fee starting at €19.99 per month. Assuming you write one post per week, a very cheap SEO consultant would do the same job for at least 10x our monthly subscription.

Our clients retain ownership of their data, so they can use WordLift’s APIs to create new services on top of their content, such as chat bots or personalized newsletters.

And last but not least, we’re partnering with WooRank to automate and combine first-in-class SEO techniques. Our goal? Let’s writers and bloggers forget about SEO rules, let AI do all the work and still… keep rocking on organic search!

The random box:

WordLift, much like today’s search engines, works with entities rather than tags and keywords. What is really an entity though?

Let’s make a simple experiment: close your eyes and imagine for a moment a…. “cat” ?; think of everything that you associate with it. In your mind’s eyes a “cat” is a mix of both generic and personalized features that make it unique. Everything you know about a “cat” is an entity in your own “knowledge graph.” You can map it to whatever language you like, but the concept remains the same and you can share it with others. Computers work the same way; a cat is an entity and can assume all kinds of forms while essentially remaining the same “thing” ?.

All the facts you care about are entities that search engines can index and learn from. Trilly and Diego, for example, are the first two cats that officially entered the web of data thanks to WordLift (and to their beloved “blogger mum” Elisabetta)! As Elisabetta started to build her own personal knowledge graph she created two “feline” entities – to share with the world her love and notion of her two pet friends.