WO2015092430A1 - Procédé, serveur, système et produit de programme informatique pour fournir un message - Google Patents

Procédé, serveur, système et produit de programme informatique pour fournir un message Download PDF

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Publication number
WO2015092430A1
WO2015092430A1 PCT/GB2014/053791 GB2014053791W WO2015092430A1 WO 2015092430 A1 WO2015092430 A1 WO 2015092430A1 GB 2014053791 W GB2014053791 W GB 2014053791W WO 2015092430 A1 WO2015092430 A1 WO 2015092430A1
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WO
WIPO (PCT)
Prior art keywords
product
web
data
server
analysis server
Prior art date
Application number
PCT/GB2014/053791
Other languages
English (en)
Inventor
Fraser Robinson
Andrew Lucas
Original Assignee
Taggstar Uk Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from GB201322568A external-priority patent/GB201322568D0/en
Priority claimed from GB201413386A external-priority patent/GB201413386D0/en
Application filed by Taggstar Uk Limited filed Critical Taggstar Uk Limited
Publication of WO2015092430A1 publication Critical patent/WO2015092430A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0253—During e-commerce, i.e. online transactions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0242—Determining effectiveness of advertisements
    • G06Q30/0244—Optimization

Definitions

  • the field of the invention relates to methods, servers, systems and computer program products for supplying a message to add to a web page from a website.
  • search engines For most web sites, the primary source of traffic is search engines. However, with so much competition and relatively little visual real estate on a search engine results page (SERP), it is extremely difficult to obtain a high search ranking. Even when a high search ranking has been achieved, it is still difficult to be the link selected and clicked by the individual given the number of search results on each page.
  • SERP search engine results page
  • CTR click through rate
  • a user of a website may see a product for sale, but decide to delay purchase, for example to search for a cheaper alternative, or to attend to other matters, only to return later to find out that the product is now out of stock. It is desirable for a user to obtain some idea about if a stock may run out, so as to better inform any decision to purchase from a website.
  • GB2420949B which includes prior art Figure 14, discloses a method of two-way communication between a web browser and a mobile telecommunication device (12) including steps of: accessing a web-site via a computer (1), sending a message to a mobile telecommunication device (12) from the web-site, and at a message server (4) capturing the IP address and port number of the computer (1), storing the temporary phone number, IP address of the computer (1) and port number of the computer (1) in a database (5), and sending the message to the mobile telecommunication device (12) with the temporary phone number.
  • an analysis server receives a request for an optimal message to add to a web page including a product, the request identifying the product; the analysis server fetches data from a database, the data relating to web server data in relation to the identified product; the analysis server analyses the fetched data so as to determine the optimal message to add to the web page including the product, and the analysis server sends the determined optimal message, in response to the request.
  • An advantage is that a user who receives the message can purchase a product before the stock runs out, whereas otherwise the user might not have made the purchase before stock runs out.
  • This can save energy (eg. computer power, communications network power) expended in searching for the product if the stock from a supplier had run out, because the product can be purchased before it has run out.
  • the stock can be assessed across a plurality of websites, it is possible for a user to ascertain that the stock is likely to run out across a set of suppliers, and in response to purchase a product before the stock runs out. This will save even more energy (eg. computer power, communications network power) expended in searching for the product if the stock had run out, because if multiple suppliers have run out of the stock, it will be even harder to find the product elsewhere.
  • a further advantage is that a web page does not have to be redesigned in multiple ways to accommodate various messages. Instead, a web page can be designed such that an optimal message can be accommodated within a standard template. This causes the server or servers which supply the web pages to operate in a new way. The effect also operates at the level of the architecture of a system of servers.
  • the method may be one in which the request identifies the product and a user, and the data relates to web server data in relation to the identified product and the user.
  • the method may be one in which the web server data is real time data.
  • An advantage is that the message sent is as up-to-date as possible.
  • the method may be one in which the analysis server receives the request from a first web server, the web server data is first web server data, and the analysis server sends the determined optimal message to the first web server, in response to the request.
  • An advantage is that the system comprising the analysis server and the first web server operates in a new way, because the system provides content that is not available from the analysis server in isolation or from the first web server in isolation.
  • a further advantage is that the message may be provided from the first web server, with minimal reconfiguration of the first web server.
  • the method may be one in which first web server data in relation to the identified product comprises web traffic data on the first web server in relation to the identified product and/ or current and future product price and availability data.
  • the method may be one including the step of the analysis server receiving web server data in relation to products from the first web server, and saving the web server data in the database.
  • the method may be one wherein types of data being collected include one or more of: purchase, audience, inventory, review, "Add to Basket” rates, purchase rates and product price.
  • the method may be one in which the analysis server also tracks all user interactions, thus enabling automated content recommendations based on shopper behavior and product interests.
  • the method may be one in which in response to receiving the message, the first web server decides whether to bid for a paid search result, and if the bid is made and won, the first web server sends the paid search result to a search engine webserver, including the message.
  • the method may be one in which the analysis server receives the request from an advertising server, and the analysis server sends the determined optimal message to the advertising web server, in response to the request.
  • the system comprising the advertising server and the first web server operates in a new way, because the system provides content that is not available from the advertising server in isolation or from the first web server in isolation.
  • the system comprising the analysis server and the advertising server operates in a new way, because the system provides content that is not available from the analysis server in isolation or from the advertising server in isolation.
  • the message may be provided from the advertising server, with minimal reconfiguration of the advertising server.
  • the method may be one in which the web server data in relation to the identified product comprises web traffic data on a plurality of web servers in relation to the identified product and/ or current and future product price and availability data.
  • the method may be one further including the step of the analysis server receiving web server data in relation to products and users, from a plurality of web servers hosting a plurality of web sites, and saving the web server data in the database.
  • the method may be one in which the advertising server cookies a user.
  • the method may be one in which the advertising server takes the text message as supplied by the analysis server and inserts it into their ad creative before the completed creative is finalized and presented to an individual shopper in their browser.
  • the method may be one in which the analysis server passes relevant product and audience data to the advertising server in real time.
  • the method may be one in which the advertising server uses RTB exchanges and uses information as to whether or not an ad contains an analysis server message to determine how much they are willing to bid for a slot.
  • the method may be one in which analysis server data messaging can be included in the creative to help increase CTR and therefore the return on investment (ROI) value to the advertiser of the ad.
  • the method may be one in which the analysis server receives the request from a web browser running on a user terminal for an optimal message to add to the web page including the product, and the analysis server sends the determined optimal message to the web browser, in response to the request.
  • An advantage is that the system comprising the analysis server and a user terminal running the browser operates in a new way, because the system provides content that is not sent out from the analysis server in isolation or which is present in the user terminal in isolation.
  • a further advantage is that the message may be provided from the analysis server, with only minimal reconfiguration of a server which is hosting the website.
  • the method may be one in which the web server data in relation to the identified product comprises web traffic data on a plurality of web servers in relation to the identified product and/ or current and future product price and availability data.
  • the method may be one further including the step of the analysis server receiving web server data in relation to products and users, from a plurality of web servers hosting a plurality of web sites, and saving the web server data in the database.
  • the method may be one in which the analysis server uses social proof to generate two distinct types of consumer sentiment: Urgency and Positive Validation; these types of messages can co-exist and appear on a page at the same time.
  • the method may be one in which the determined optimal message includes a standard width UI message, and/ or a narrow width UI message.
  • the method may be one in which the determined optimal message includes text and/or graphics.
  • the method may be one in which the analysis server includes an algorithm that identifies increases in the rate of sale of products.
  • the method may be one in which the web server provides messages in page.
  • the method may be one in which the web server provides messages as informational balloons that can fade in/ out, or slide in/ out.
  • the method may be one in which a position of the message on the web page is varied by the analysis server based on performance.
  • the method may be one in which the web server displays the message at one or more of the following stages: home page, Search results /gallery page, Product page, Basket section.
  • the method may be one in which the message is applied in display advertising.
  • the method may be one in which the message is applied in search results: in natural or paid search.
  • the method may be one in which if the web server is able to map the visitor back to an email address, then that web server can follow up with an email to the individual that contains personalized content.
  • the method may be one in which the method is used in personalized television advertising.
  • the method may be one in which code is installed in a website, to collect website data.
  • the method may be one in which the code is JavaScript code.
  • the method may be one in which the optimal message includes one or more of "how many others are looking at this product", “when was the last one purchased”, “how many have been booked today” and “what do others think of this”.
  • the method may be one in which the analysis server includes machine-learning algorithms that dynamically test and optimise performance.
  • the method may be one in which the machine-learning algorithms vary one or more of: data thresholds, message combinations, message tone, message design or colour, the number of messages, duration of a balloon on a web page, position of message on page.
  • an analysis server configured to supply an optimal message to add to a web page from a website, in which: the analysis server is configured to receive a request for an optimal message to add to a web page including a product, the request identifying the product; the analysis server is configured to fetch data from a database, the data relating to web server data in relation to the identified product; the analysis server is configured to analyse the fetched data so as to determine the optimal message to add to the web page including the product, and the analysis server is configured to send the determined optimal message, in response to the request.
  • the analysis server of the second aspect of the invention may be configured to perform a method according to any aspect of the first aspect of the invention.
  • a computer program product arranged such that when running on an analysis server, the computer program product is configured to supply an optimal message to add to a web page from a website, the computer program product arranged to: receive a request for an optimal message to add to a web page including a product, the request identifying the product; fetch data from a database, the data relating to web server data in relation to the identified product; analyse the fetched data so as to determine the optimal message to add to the web page including the product, and send the determined optimal message, in response to the request.
  • the Computer program product according to the third aspect of the invention may be configured to perform perform a method according to any aspect of the first aspect of the invention.
  • a system for supplying an optimal message to add to a web page from a website comprising an analysis server and a first web server in connection with the analysis server, in which: the analysis server is configured to receive from the first web server a request for an optimal message to add to a web page including a product, the request identifying the product; the analysis server is configured to fetch data from a database, the data relating to first web server data in relation to the identified product; the analysis server is configured to analyse the fetched data so as to determine the optimal message to add to the web page including the product, and the analysis server is configured to send the determined optimal message to the first web server, in response to the request.
  • a system for supplying an optimal message to add to a web page from a website comprising an analysis server and an advertising server in connection with the analysis server, in which: the analysis server is configured to receive from the advertising server a request for an optimal message to add to a web page including a product, the request identifying the product; the analysis server is configured to fetch data from a database, the data relating to web server data in relation to the identified product; the analysis server is configured to analyse the fetched data so as to determine the optimal message to add to the web page including the product, and the analysis server is configured to send the determined optimal message to the advertising server, in response to the request.
  • a system for supplying an optimal message to add to a web page from a website comprising an analysis server and a user terminal running a web browser, the user terminal in connection with the analysis server, in which: the analysis server is configured to receive from the web browser a request for an optimal message to add to a web page including a product, the request identifying the product; the analysis server is configured to fetch data from a database, the data relating to web server data in relation to the identified product; the analysis server is configured to analyse the fetched data so as to determine the optimal message to add to the web page including the product, and the analysis server is configured to send the determined optimal message to the web browser, in response to the request.
  • a method of supplying an optimal message to add to a web page comprising the steps of: (i) an analysis server receiving a request from a web browser running on a user terminal for an optimal message to add to a web page including a product, the request identifying the user;
  • the analysis server fetching data from a database, the data relating to web server data in relation to the identified product or the user;
  • the method may be one in which the web server data is real time data.
  • the method may be one in which the web server data in relation to the identified product or user comprises web traffic data on a plurality of web servers in relation to the identified product or user and/ or current and future product price and availability data.
  • the method may be one further including the step of the analysis server receiving web site traffic data in relation to products and users, from a plurality of web servers hosting a plurality of web sites, and saving the web site traffic data in the database.
  • an analysis server configured to supply an optimal message to add to a web page, the analysis server configured to:
  • the analysis server may be further configured to perform the method according to any aspect of the fourth aspect of the invention.
  • a computer program product executable on an analysis server, the computer program product when running on the analysis server arranged to supply an optimal message to add to a web page, the computer program product configured to:
  • the computer program product may be further configured to perform the method according to any aspect of the fourth aspect of the invention.
  • a seventh aspect of the invention there is provided a method of supplying product recommendations and associated web links to add to a web page from a website, comprising the steps of:
  • an analysis server receiving from a website server a recent activity record of a user who has been accessing the website on the website server, and an identification of the user;
  • the analysis server in response to the determination that the user is likely to leave the website soon, uses the identification of the user to generate a set of product recommendations of third party products, together with web links to third party websites which supply the third party products, and (iv) the analysis server sending the set of product recommendations of third party products, together with the web links to the third party websites which supply the third party products, to the website server, for inclusion in the web page from the web site.
  • the analysis server may be provided.
  • a computer program product executable on the analysis server so as to perform the method according to the seventh aspect of the invention may be provided.
  • a method of supplying product recommendations and associated web links for inclusion in a web page from a website comprising the steps of:
  • an analysis server receiving from a web browser running on a user terminal a recent activity record of the user who has been accessing a website, and an identification of the user;
  • the analysis server in response to the determination that the user is likely to leave the website soon, uses the identification of the user to generate a set of product recommendations of third party products, together with web links to third party websites which supply the third party products, and
  • the analysis server sending the set of product recommendations of third party products, together with the web links to the third party websites which supply the third party products, to the web browser, for inclusion in the web page from the web site.
  • the analysis server may be provided.
  • a computer program product executable on the analysis server so as to perform the method according to the eighth aspect of the invention may be provided.
  • a method of supplying data suitable for including in a web page including a product comprising the steps of:
  • the analysis server fetching data from a database, the data relating to web traffic in relation to the product; (iii) the analysis server analysing the fetched data so as to determine data suitable for adding to the web page including the product, and
  • the method may be one further comprising the steps of:
  • the advertising web server including the data into a pre-configured unit relating to the data and to the product so as to create a message
  • the analysis server may be provided.
  • a computer program product executable on the analysis server so as to perform the method according to the ninth aspect of the invention may be provided.
  • the servers referred to in this document may be stand-alone, real, virtual or in the cloud, as would be clear to one skilled in the art.
  • Figure 1 shows examples of Standard Width UI Messages (Desktop and Tablet).
  • Figure 2 shows examples of Narrow Width UI Messages (Mobile).
  • Figure 3 shows an example of an Audience Rule Table.
  • Figure 4 shows an example of a Purchase Rule Table.
  • Figure 5 shows an example in which balloon overlays fade in then out, informing the shopper without intruding and in-page, real time messaging is provided, displayed on a fixed computer.
  • Figure 6 shows an example in which messaging in listings pages helps drive discovery and call to action, displayed on a fixed computer.
  • Figure 7 shows an example of driving conversion in mobile devices too, displayed on a mobile phone.
  • Figure 8 shows an example in which a mobile data banner fades in then out, and in-page messaging is provided, displayed on a mobile phone.
  • Figure 9 shows an example in which an analysis server dynamically replaces some or all of a retailer's own product recommendations and suggests related products from 3rd party retailers instead, in the box.
  • Figure 10 shows an example of a system, in which fixed user terminals 1 to n are in connection with the internet, and mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a website server for site A, a search engine X server and a Taggstar server are in connection with the internet.
  • Figure 11 shows an example of a system, in which fixed user terminals 1 to n are in connection with the internet, and mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a first website server, a second website server, an advertiser server and a Taggstar server are in connection with the internet.
  • Figure 12 shows an example of a system, in which fixed user terminals 1 to n are in connection with the internet, and mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a website server for site A, website server for site B and the Taggstar server are in connection with the internet.
  • Figure 13 shows an example of a system, in which fixed user terminals 1 to n are in connection with the internet, and mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a first website server, an advertiser server and a Taggstar server are in connection with the internet.
  • Figure 14 shows a prior art communication system disclosed in GB2420949B, including a mobile telecommunication device (12), a computer (1), the internet (2), a web server (3), a message server (4), and a database (5).
  • Taggstar improves shopping conversion and drives user engagement by providing real time social proof and persuasive messaging and content recommendations on web sites, as well as in offsite marketing. For example, informing shoppers about “how many others are looking at this product”, “when was the last one purchased”, “how many have been booked today” and “what do others think of this”, helps to inform a buying decision while creating a sense of urgency that delivers superior shopping conversion.
  • Taggstar also tracks all user interactions, thus enabling automated content recommendations based on shopper behavior and product interests. This type of information is often referred to as 'social proof or 'persuasive messaging' and appeals to the behavioral psychology of consumers, in examples such as:
  • Taggstar analyses all the available information on a page and distills it down to key messages that help the shopper to make a fast and informed buying decision. For example, product reviews are hugely valuable, but they are often verbose and too numerous to read. For example, a product may have 35 extensive reviews, star ratings and "would/would not recommend" data points.
  • Taggstar analyses the available review data and for example informs the shopper in a simple manner such that for example "80% of reviewers gave this 5 stars.”
  • Taggstar analyses large amounts of online data in real time and generates the message, or combination of messages, that drives the most positive outcome. In eCommerce, that outcome is typically an increase in sales conversion, or greater customer engagement, as measured by some kind of desired action such as click rate.
  • Taggstar uses social proof to generate two distinct types of consumer sentiment:
  • Urgency few things are more annoying to the consumer than realizing they've missed out on a purchasing opportunity ("fear of missing out"), usually because a product is out of stock. Hesitation, the desire to price compare elsewhere or wanting to research a product further are often reasons for delaying a purchase decision. However, providing inventory information is only part of the story. Knowing when a product was last purchased, how many have sold today and how many people are looking at it right now gives greater context to the "how many are left" data point, driving faster decisionmaking on the part of the consumer, and higher sales conversion.
  • Positive Validation social proof also inspires consumer confidence in a particular product choice by letting them know certain types of validating information: a. Perennial best seller: "Great choice! This one is a customer favourite and always sells well.
  • Taggstar uses both Urgency and Positive Validation to help inform the customer about the product they are considering purchasing. These types of messages can co-exist and appear on a page at the same time.
  • Taggstar by tracking the number of people who are looking or have looked at specific product pages, Taggstar can communicate that data back to the shopper, thus giving a sense for how much 'buzz' or activity there is around products.
  • Taggstar tracks a number of other data points for reporting purposes, "Add to Basket" rates, purchase rates and product price.
  • Narrow UI Messages (Mobile) (e.g. en-GB locale)
  • Messaging is typically abbreviated for the narrow UI (i.e. mobile) so as to reduce word count: see Figure 2 for examples.
  • Taggstar have developed an algorithm that identifies increases in the rate of sale of products, the objective being to highlight increases in rates of sale through the display of a 'selling fast' user interface (UI) message.
  • the ultimate objective being to generate visitor add to basket uplift.
  • the algorithm filters out over 90% of 'low volume' products that have less than 10 purchases in a 48 hour window as these products do not large have large enough increases in rates of sale for them to be highlighted as 'hot'.
  • An increase in the quantity purchased over 48 hours value from 2 to 3 does not make a product 'hot' despite that fact that this is a 50% increase.
  • Taggstar uses social proof messaging to influence consumer behavior both on the client's web site ("Onsite”), as well as away from the web site (“Offsite”).
  • Examples of offsite uses of data include in display advertising and search.
  • Onsite Messaging Taggstar delivers onsite messaging that is visible to a web site visitor in two key ways:
  • Balloons serves informational balloons that can fade in/ out, or slide in/ out. Balloons can be positioned anywhere on a page, with variable colours, message types, speed of appearance/ disappearance etc.
  • Onsite data can be displayed to a visitor to a web site in a number of sections of a web site.
  • this means persuasive messaging can appear at different stages of the shopping funnel, as summarized below: a) Home page— modules displaying most recently purchased items, trending items and products getting a lot of activity help engage people who have just arrived at the site, while building a feeling of trust to those who may be new to that particular brand. Knowing that others are purchasing from a site gives a prospective customer confidence.
  • Search results /gallery page the search results page is a key area of any eCommerce site in that the customer has declared an interest in a specific product or product type.
  • Product page the product page or product detail page is where the shopper can consume the most detailed content that relates to a product. It is here that customer reviews, detailed product description, multiple images, video, detailed delivery options and so on are all available. It is here that the all-important "Buy” or "Add to basket” button typically appears. By including real time persuasive messaging on this page, the retailer is able to drive a higher conversion rate.
  • Offsite messaging Taggstar's real time data messaging can be applied to all types of marketing materials, broken down into two key segments:
  • Display advertising Includes standard display formats (e.g. banners, skyscrapers, mid page units (MPUs)), ad retargeting, email campaigns, television and non virtual formats such as digital billboards.
  • standard display formats e.g. banners, skyscrapers, mid page units (MPUs)
  • MPUs mid page units
  • Standard display ad formats include banners, skyscrapers and MPUs. Standard display ads often target individuals based on location, demographics, subject matter of publisher where the ad appears.
  • Performance of display ads is based on click through rate (CTR).
  • CTR click through rate
  • RTB real time bidding platforms
  • Taggstar data messaging can be included in the creative to help increase CTR and therefore the return on investment (ROI) value to the advertiser of the ad.
  • Advertisers using RTB exchanges could potentially take the information as to whether or not an ad contains Taggstar data to determine how much they are willing to bid for a slot (i.e. if you know a piece of creative contains Taggstar data that improves performance, then perhaps bid more for the media).
  • Ad Retargeting is an online advertising technology that serves customized ads to people who have indicated an interest in a product on your website. This differs from standard display advertising in that retargeted individuals will see ads for a product they have already looked at when they navigate away to a third party site. For example, a shopper who views a pair of jeans on site A, might see an ad for that same pair of jeans when visiting site B. Clicking the ad would take the shopper back to the jeans product page on Site A.
  • Taggstar aims to use the real time audience and product information it is capturing from retailers to optimize the performance of ad retargeting creative. Emphasis here is on the real-time nature of the data. This is achieved by including persuasive messaging in the ad creative itself.
  • retargeted ad creative currently displays an image of the jeans, together with the price and retailer in hopes of triggering a click response from the shopper.
  • Taggstar provides the retargeting business with snippets of text to include in the ad creative.
  • the result is that the new creative would show the thumbnail image of the jeans, the price, the retailer, and now, the Taggstar data, such as: "50 people have looked at these jeans since you did.”
  • This type of information and messaging drives an increase in ad Click Through Rate (CTR) and thus improved ROI for the retargeting business and advertiser.
  • CTR Click Through Rate
  • Email remains one of the most high-performing marketing channels and within that channel, email can be used in much the same way that display retargeting works.
  • Taggstar social proof messaging By including Taggstar social proof messaging, the engagement rates of retargeted emails can be improved.
  • Non Virtual Billboards As television migrates online and becomes increasingly personalized, consumers will find themselves able to respond to advertising in real time. This could include engaging with a TV advertisement that leads directly to a purchase on the same screen. Retailers and brands will be able to use Taggstar's real time social proof technology to populate television advertising, much in the same way that it does standard display. This becomes possible as the television industry migrates towards ad serving technology only previously seen online. 5. Non Virtual Billboards
  • Taggstar For Taggstar to work with retargeting, the retailer/ advertiser in question must have both Taggstar's JavaScript code and the retargeter's tracking pixel installed.
  • Taggstar When Taggstar is installed on a site (e.g. the first website server of Figure 11), data is being collected in order to deliver the persuasive messaging.
  • the ad platform or retargeter e.g. the Advertiser server of Figure 11
  • the ad platform or retargeter cookies the customer and collects data pertaining to which specific products they've looked at so that when that customer navigates away to a different third party site (e.g. second website server of Figure 11) within the Advertiser's ad network, they are able to serve up an ad displaying one of the products already viewed.
  • the Advertiser When the Advertiser has identified a customer, they match the correct product image (e.g. jeans) to that customer and push a bespoke advertisement.
  • the Advertiser simultaneously calls the Taggstar application programming interface (API) (e.g. on the Taggstar server of Figure 11) with the product identification (ID).
  • Taggstar takes the product ID and uses it to gather the relevant audience and purchase data that relates to that specific product. Once the data has been assembled by Taggstar, the most effective type of message is automatically selected, the text is assembled and then instantly passed back to the Advertiser (e.g. the Advertiser server of Figure 11) via API.
  • API application programming interface
  • the Advertiser (e.g. the Advertiser server of Figure 11) takes the text message as supplied by Taggstar (e.g. the Taggstar server of Figure 11) and inserts it into their ad creative before the completed creative is finalized and presented to the individual shopper in their browser.
  • Taggstar e.g. the Taggstar server of Figure 11
  • An example system implementing the invention is shown in Figure 11.
  • fixed user terminals 1 to n are in connection with the internet
  • mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a first website server, a second website server, an advertiser server and a Taggstar server are in connection with the internet.
  • Taggstar e.g. on the Taggstar server of Figure 11
  • Web Browser e.g. running on one of the fixed user terminals or mobile user terminals of Figure 11
  • Taggstar can pass the data message directly back to the Web Browser. From a customer/ end-user perspective, the end result is the same. This is simply a different way of managing the flow of information between customer, Advertiser and Taggstar.
  • An example system implementing the invention is shown in Figure 11.
  • Taggstar's challenge is to pass the relevant product and audience data to the Advertiser in real time, for them to include when ad creative is pushed to the consumer.
  • Site B allows display advertising and is within the Advertiser's ad network.
  • v. Advertiser identifies the Shopper as having previously looked at the Jeans on Site A and prepares to show the Shopper a display ad (e.g. banner, skyscraper, mid page unit (MPU)) promoting the Jeans.
  • ad e.g. banner, skyscraper, mid page unit (MPU)
  • Advertiser (or Web Browser) calls the Taggstar API, supplying the product ID for the Jeans.
  • Taggstar returns the most appropriate message directly to either the Advertiser or Web Browser. This message is made up of real time audience, purchase and review data that pertains to those jeans at the time the ad is served. Key here is that this information is not generic, but relates to the product and its real time (i.e. right now) performance.
  • Advertiser or Browser receives the optimal message from Taggstar and includes it in the ad, along side the other information that makes up the creative (e.g. thumbnail image of jeans, price, retailer etc).
  • Taggstar audience and product data can be applied to display advertising and retargeting to improve media performance
  • the same data can be used to optimize the click rates of natural and paid search results on search engines like Google and Bing.
  • search engines For most web sites, the primary source of traffic is search engines. However, with so much competition and relatively little visual real estate on a search engine results page (SERP), it is extremely difficult to obtain a high search ranking. Even when a high search ranking has been achieved, it is still difficult to be the link selected and clicked by the individual given the number of search results on each page.
  • SERP search engine results page
  • a high search ranking in Natural (i.e. not paid) search results is typically achieved through Search Engine Optimisation (SEO).
  • SEO Search Engine Optimisation
  • a high ranking in Paid Search results can be obtained by bidding the highest Cost Per Click (CPC) amount for key terms.
  • CPC Cost Per Click
  • travel businesses might bid on searches for "flights to New York”.
  • CPC rates vary wildly based on variables that include business vertical, conversion rates, margin and so on. Those who have bid the most for traffic will appear at the top of the paid search listing. As you move down the list, the price being offered is lowered, based on the notion that those at or near the top tend to get the most clicks.
  • Taggstar provides including audience and purchase information in SERPs, such as "how many people are looking at this right now", “how many have sold recently” as a means to drive customer awareness and draw them to a particular store.
  • This kind of shopper psychology is often referred to as “social proof, and is based on the notion that consumers prefer a busy/ popular retailer (or restaurant) to one that is empty.
  • Taggstar believes that the inclusion of this data improves the CTR of both natural and paid search links. This in turn will increase the ROI of paid search marketing spend by online advertisers.
  • Taggstar provides an API that delivers messaging into advertising to help improve the performance of the ad.
  • sites who wish to use Taggstar data in their search results listings need to have the Taggstar JavaScript snippet installed on their site.
  • Browser for example on a user terminal of Figure 10
  • Search Engine X for example on search engine X server of Figure 10
  • types a search e.g. "Samsung Galaxy S4 phone".
  • Ecommerce "Site A” (for example, on website server for site A of Figure 10) sells this particular product and has bid on the search term "Samsung Galaxy S4 phone" on Search Engine X.
  • Site A ad management platform calls the Taggstar data API (for example on Taggstar server of Figure 10), providing the product ID of the Samsung Phone.
  • Taggstar uses that product ID to fetch the related audience and purchasing data for the Samsung Galaxy S4 phone on Ecommerce Site A.
  • v. Taggstar then analyses the data it has about the Samsung Galaxy 4 phone on Site A and determines what type of message will be most beneficial to improving the performance of the ad.
  • Taggstar returns the data to Site A ad management platform.
  • Site A decides if a bid will be made, and the price of the bid. If a bid is made and won, the SERP loads with Site A's link/ ad, which includes the Taggstar message.
  • FIG. 10 An example system implementing the invention is shown in Figure 10.
  • fixed user terminals 1 to n are in connection with the internet
  • mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a website server for site A a search engine X server and a Taggstar server are in connection with the internet.
  • the ad management platform can dynamically alter the price it's willing to bid based on whether or not Taggstar data is available and performing.
  • Taggstar's performance is measured by its ability to improve shopping conversion, as well as browser return rates (e.g. if a customer typically returns 48 hours later to purchase a product they have previously looked at, Taggstar aims to shorten this to less than 48 hours. This is because the customer has a sense for a product's popularity and not wanting to miss out).
  • Taggstar constantly measures performance of the different message types, balloon colours and even sentence structure of messaging in order to determine which information delivers the best result.
  • Data thresholds a customer responds differently to a message depending on the numbers that message contains, even when the fundamental message type remains the same. For example, informing a customer that "20 people have bought one in the last 2 hours” is more compelling than saying "2 people have bought one in the last 48 hours”. But with the multitude of different message types, the variance between the performance of those messages is more nuanced. This is where Taggstar continually monitors not only the message types that drive the best response, but also the point at which the performance of a message type shifts based on the numbers it contains. 2.
  • Taggstar delivers messages to the site visitor about based on audience data, purchase data and review data for individual products in an online store.
  • the combination of different message types can deliver significantly improved performance. For example, telling a customer that "3 others are looking at this right now” can influence purchase behavior up to a point. But by introducing another data point, so the message now reads "3 others are looking at this right now and 5 have bought one in the last 2 hours” can significantly improve the customer's decision to purchase.
  • Taggstar monitors the effect different combinations of message type have on consumer behavior and thus biases the messaging on those learnings.
  • Number of messages given the various message types available, Taggstar experiments with delivering multiple messages. These can all be contained in one balloon (e.g. "3 people are looking at this right now and we've sold 5 in the last 30 minutes"), or in multiple balloons, where each balloon contains a single message type (e.g. "3 people are looking at this right now” might appear in one balloon, and "We've sold 5 in the last 30 minutes” could appear as a second balloon).
  • Taggstar data has applications to all types of web site, whether commercial or not. However, there are certain verticals where we believe its use will be particularly effective: Retail; Travel; Property; Job search; Finance.
  • Taggstar is simple to install and requires a snippet of JavaScript to be copied and pasted into the HTML of your site template, as described below:
  • JavaScript should also be copied and pasted into the template of all confirmation pages (in any part of the HTML, preferably before the closing ⁇ /head> tag). This allows Taggstar to generate data messaging pertaining to purchases.
  • Taggstar is designed for desktop and mobile web and the JavaScript should therefore be installed in both areas.
  • An API is available for use in your native mobile application.
  • Taggstar will provide separately configured snippets of JavaScript. This allows for local language messaging, as well as distinct reporting.
  • Taggstar's in-house UI team will create and implement all bespoke designs to suit the look and feel of the particular brand.
  • Taggstar's platform can be hosted in the Amazon EC2 Cloud and can be scaled horizontally to manage any traffic spikes or seasonal trends seamlessly.
  • Some examples of the data points Taggstar is capturing when installed on a web site.
  • a Software -as-a-Service system providing a HTTP interface to JavaScript tag code executed by web browser applications having a method of storing data in a database and processing data.
  • a HTTP web server making available an E-Commerce web site where purchases can be made for goods or services.
  • Any service operated for the purpose of displaying Internet advertising Any service operated for the purpose of displaying Internet advertising.
  • the Taggstar Real Time Message System (the 'system' hereafter) displays 'persuasive' messages on the product pages of a Retailer's E-commerce web site.
  • the objective of the system is to increase the Retailer revenues, when measuring revenue from those Visitors who view persuasive messages compared to those Visitors that do not. This measurement is achieved using A/B testing methods.
  • the system must be integrated with two Visitor use cases that occur on the Retailer's E- commerce site.
  • Use Case 1 Visit Product Web Page Use Case
  • the goal of the Visitor is to obtain information about a product and, or, to add the product to a basket/ cart.
  • the main mechanisms of the system in this use case are: i ) record the visit event for the purpose of displaying the data point, either singularly, or aggregated with other events of the same type, within a persuasive message. ii) display one or more persuasive messages within the product web page to the Visitor to influence the visitor to purchase the product.
  • Use Case 2 Order Confirmation Web Page Use Case
  • the goal of the Retailer in this use case is to inform the Visitor that their order been completed successfully and no further steps are required by the Visitor. This is generally achieved by displaying an 'Order Confirmation Web Page' containing information such as an order identifier.
  • the main mechanism of the system in this use case is: i ) record the order event for the purpose of displaying, either singularly, or aggregated with other events of the same type, within a persuasive message. Integration Model
  • the Real Time Message System integrates with the Retailer's web site through the use of JavaScript tag code, supplied by Taggstar to the Retailer.
  • the JavaScript tag code is placed into Web Page content either directly, i.e. by the Retailer's Web Server including the tag in the HTML response body of a Web Page, or indirectly, by a Tag Management application (e.g. Google Tag Manager).
  • the JavaScript tag code is customised by Taggstar for each Retailer by the inclusion of an unique identifier, the 'Retailer Web Site ID' that is transmitted to the Real Time Message System to enable identification of the Retailer's web site.
  • JavaScript tag code uses the 'bootloader' pattern, i.e. it is a relatively small amount of code designed to load additional JavaScript depending on the execution environment, including, but not limited to :
  • the type of web page e.g. product page or order confirmation page
  • the device e.g. mobile device or desktop.
  • the function of the JavaScript tag code is :
  • JavaScript tag code Additional functions include :
  • a Product Web Page on a Retailer Web Site is requested by a Visitor using a web browser application.
  • the Product Web Page content is processed by the Visitor's web browser and the Taggstar JavaScript tag code is executed that a) downloads any additional JavaScript required and b) makes a request to the Real Time Message System for persuasive messages strings and c) displays in the web page any message strings returned by the Real Time Message System.
  • the Taggstar JavaScript tag code monitors the UI element that triggers an 'add to basket' action and the Visitor triggers this action, makes a request to the Real Time Message System to log this information along with the details of the Visitor. Order Confirmation Page
  • An Order Confirmation Page on a Retailer Web Site is requested by a Visitor using a web browser application.
  • the Order Confirmation Page content is processed by the Visitor's web browser and one or more Taggstar JavaScript files are requested and then executed that then extracts order and product information, such as identifier and price, from the web page and makes a request to the Real Time Message System to record the order event data along with the details of the Visitor (including but not limited to a Visitor ID, a session ID).
  • order and product information such as identifier and price
  • the system continuously calculates 'audience' measures for products on a Retailer's web site.
  • An audience measure is an integer value that is equal to the size of the set of sessions related to a product at a point in time.
  • a session ID is created as a composite ID, comprising a Visitor ID and a Product ID, allowing the set of sessions for a given product ID to be easily discovered. It is possible for the set of sessions to be an empty set.
  • Session has its normal meaning in the context of a software application, i.e. a means of identifying a time ordered series of events, where no event in the session is separated from any other event in the session by more than N units of time, where N is a duration referred to as the 'session expiry time'.
  • a session is said to have expired when the time between the last event in the session and the current time is greater than the session expiry time.
  • the audience measure used by the system excludes expired sessions.
  • the system creates and maintains two sets of sessions. One to calculate a 'current' audience measure and one to calculate a 'recent' audience measure.
  • the current audience measure uses sessions with an expiry time of 20 minutes and the recent audience measure uses sessions with an expiry time of 2 hours.
  • Visitor Use Case 1 Creation and Update of an Audience Session
  • Trigger A Visitor requests a given product page a) IF the Visitor [1] has not requested the product page with the last N minutes THEN i) Create a session timer [2], initialised to N minutes, and identified by the combination of the visitor ID and the product ID. ii) Increment the audience counter for the product by 1. b) ELSE IF the Visitor has requested the product page within the last N minutes THEN i) Lookup the session timer identified by the visitor ID and product ID
  • a session timer ID is a composite ID, comprising a Visitor ID and a Product ID.
  • a session timer counts down from the value it is initialised to, or reset to, and upon reaching zero decrements by 1 the audience counter for the related product (identified by the product ID obtained from the timer's composite ID). After reaching zero the timer has no further use in the system and at some point is destroyed by the system application.
  • the system records purchases for Retailer products that occur during the Order Confirmation Page Use Case.
  • the system calculates the quantity of purchases in the last N days for all products at frequent intervals as a background process.
  • a request is made to the Real Time Message System and the response may include zero, or one or two persuasive messages strings that are the result of an execution of a set of rules that determine the most persuasive message to be displayed to a visitor.
  • the set of rules comprises of two tables, one for each category of message, audience and purchase. No more than one message per category is returned on the response.
  • Rule trigger conditions are evaluated in ascending order by rule priority within a table.
  • Rule trigger condition evaluation within a table stops when evaluation of a trigger condition returns true, then at that time, the persuasive message string corresponding to the trigger, is generated by replacing a placeholder in the message template, shown as ⁇ ⁇ variable ⁇ ⁇ , with the variable used in the trigger condition, and the resulting string is added to the response (e.g. for display in the Visitor web browser).
  • Pseudo Code product retrieve product from database using ID included in the request made by the JavaScript tag.
  • the product has associated with it variables current_audience, recent audience and quantity of purchases, as described in this document.
  • last_purchase_date that is the date of the last purchase of the product, and quantity purchased that is the quantity of purchases within the last N days.
  • the goal of the Advert System is to increase the Click Through Rate (CTR) of Retailer adverts by providing to an Ad Platform persuasive messages and data generated by the Real Time Message System.
  • CTR Click Through Rate
  • the function of the Advert System is act as interface between the Real Time Message Server and an Ad Platform.
  • the Advert System for example, the Taggstar server of Figure 13
  • an Ad Platform API for example, hosted in the advertiser server of Figure 13
  • Updates may occur regularly or be triggered by changes in the product data, for example, by current audience increasing by X %, or by a change in quantity of purchase rate for a product.
  • the data points are incorporated within natural language sentences or graphic images by the Ad Platform (for example, hosted in the advertiser server of Figure 13), into the pre- configured advert units created by the Retailer (for example, whose website is hosted on the first website server of Figure 13), and served by the Ad Platform to Internet users (for example, users of user terminals shown in Figure 13) who meet the advert targeting criteria specified by the Retailer.
  • the Ad Platform for example, hosted in the advertiser server of Figure 13
  • the Retailer for example, whose website is hosted on the first website server of Figure 13
  • Internet users for example, users of user terminals shown in Figure 13
  • a pre-configured advert must contain meta data specifying a product ID from the Retailer web site.
  • the Advert System uses the Advert meta data to match an advert with a Retailer product. This also allows the Advert System to obtain from the Real Time Message System data points for a specific product. Once the data points are obtained for a product, the Ad Platform API is used to update the pre-configured Advert for the product.
  • FIG. 13 An example system implementing the invention is shown in Figure 13.
  • fixed user terminals 1 to n are in connection with the internet
  • mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • a first website server, an advertiser server and a Taggstar server are in connection with the internet.
  • the Ad Platform connects to the Advert System when an Internet user who meets the targeting criteria for the advert created by the Retailer, and the Advert System returns data points including current audience, recent audience and quantity of purchases, that are then incorporated as text or graphic images into the advert unit served to the Internet user.
  • a product ID In an API made by the Ad Platform to the Advert System, a product ID must be specified to enable the data points to be obtained from the Advert System and returned to the Ad Platform.
  • Balloon overlays fade in then out, informing the shopper without intruding.
  • real time messaging is provided. See Figure 5 for example, displayed on a fixed computer.
  • Driving conversion is provided in mobile devices too. See Figure 7 for example, displayed on a mobile phone. Mobile data banner fades in then out. In-page messaging is provided. See Figure 8 for example, displayed on a mobile phone.
  • Reports includes traffic, product popularity, purchase rates, conversion uplift, messaging coverage.
  • Taggstar's customer "scoring" algorithm identifies:
  • Taggstar dynamically replaces some or all of your own product recommendations and suggests related products from 3rd party retailers instead. See box in Figure 9 for example, which may include: "You may also like"
  • a user of a terminal such as a fixed terminal (e.g. fixed user terminal 1 of Figure 12) or a mobile terminal (e.g. mobile user terminal 1 of Figure 12), views items for purchase on website A (eg. on website server for site A of Figure 12).
  • website A e.g. on website server for site A of Figure 12
  • Browser for example on a user terminal of Figure 12 goes to website A (for example on website server for site A of Figure 12) and provides views of products for sale.
  • Website A management platform calls the Taggstar data API (for example on Taggstar server of Figure 12), sending the recent activity record of the user.
  • Taggstar uses that activity record to determine that the user is likely to leave website A soon.
  • the Taggstar product recommendation engine generates third party paid product recommendations suitable for the user who is likely to leave website A soon.
  • the Taggstar server sends the generated third party paid product recommendations suitable for the user who is likely to leave website A soon to the website A management platform, including links to third party websites (eg. website server for site B of Figure 12) which sell the recommended third party paid products.
  • Site A sends to the browser the received third party paid product recommendations suitable for the user who is likely to leave website A soon, including links to third party websites which sell the recommended third party paid products.
  • An example system implementing the invention is shown in Figure 12.
  • fixed user terminals 1 to n are in connection with the internet
  • mobile user terminals 1 to m are in connection with the internet, such as via cellular networks or via wifi networks.
  • website server for site A, website server for site B and the Taggstar server are in connection with the internet.
  • Taggstar's intelligent platform decides what kind of message works best for a product, depending on volume and frequency of views, purchases and we can provide recommendations as well. There are many ways to construct persuasive messaging, even around lower volume products.
  • Taggstar aims to drive higher customer engagement and shopping conversion uplift by displaying real time messaging about products directly to shoppers on your site.
  • Taggstar's JavaScript has already been supplied and installed by ExampleCompany. Our preference is to be installed as broadly as possible, to allow for a large data set.
  • Taggstar will track data independently using your A/B split.
  • Taggstar can interpret the data correctly.
  • a JavaScript global variable called 'taggUserExperimentGroup' should be created in each page containing either 'control' or 'treatment' string values and this variable must be present on every page impression where Taggstar messaging could be displayed.
  • KPIs key performance indicators
  • Taggstar will gather data points and report weekly on a number of different queries, including:
  • Project Hotcake is a business to business (B2B) product that creates a sense of shopper urgency on e-commerce sites, thereby driving greater engagement and shopping conversion.
  • Urgency is generated by providing real-time information about a product to the shopper, such as how many other people are looking at the same product right now, how many purchases have been made recently, and how many are left.
  • Messaging may be delivered in the native language of the site on which we are running. It does not need to adapt to the language of where the shopper is located.
  • Clients may require monthly reporting that shows the following daily data: 1. Total page impressions.
  • Self sign up ecommerce businesses could create an account, self sign up, generate the JS, customize the UI with colour and font, enter payment details and then install.
  • Retargeting data if a shopper looks at a hotel in New York, retarget them later on a third party site (via Criteo etc) saying how many people have booked that hotel in the last 24 hours (for example)
  • Number in stock / rate of purchase means we could estimate when it could go out of stock eg going fast at this rate, they'll be gone by Thursday.
  • Taggstar will gather the data points and report weekly based on a number of different queries, including:
  • Balloon message Types a) current audience (with hot style)
  • Configuration Variables current_audience_count unique visitor count for a product within last 20 minutes - 1 (-1 to avoid counting the user currently viewing the page).
  • the 20 minute window should be a global variable.
  • recent_audience_count unique visitor count for a product within last 2 hours - 1.
  • the 2 hours window should be a global variable.
  • purchases_display_threshold - if number of purchases with N hours is less then this threshold then the purchase message is not displayed (as showing low numbers is not a persuasive message).
  • the purchase_display_threshold is hard coded as '3' in version 0.1 but will be per site in later versions. N, the number of hours, will be a per site variable. purchases_count - number of checkouts for a product within N hours. This will be site specific.
  • This variable will be per site and hardcoded in version 0.1, and could be dynamically set in later versions.
  • ExampleComapny do not want to display a last purchase message when the purchase was made over one hour ago. Review Message Rules
  • ExampleComapny may make this message be displayed as follows - In preference to the audience message on secondwebsite.com where review data available and display rule evaluates to true
  • ExampleComapny General Information 1 Product messaging for reviewed items are displayed on firstwebsite.com and secondwebsite.com.
  • the review message on firstwebsite.com is X% of reviewers recommended this item
  • the review message on secondwebsite.com is X% of reviewers rated this item Y stars
  • the 0.1 messaging must include a review message type delivered by taggstar a) Scraping review data -
  • Secondwebsite.com has the review syntax (powered by pluck) that will be used throughout ExampleComapny sites in the future.
  • Style of messaging Messaging UI style should match the existing style, as shown on the firstwebsite.com pages.

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Abstract

L'invention concerne un procédé visant à fournir un message optimal à ajouter à une page web issue d'un site web, au cours duquel: un serveur d'analyse reçoit une demande portant sur un message optimal à ajouter à une page web comprenant un produit, la demande identifiant le produit; le serveur d'analyse extrait des données d'une base de données, les données se rapportant à des données de serveur web en relation avec le produit identifié; le serveur d'analyse analyse les données extraites de façon à déterminer le message optimal à ajouter à la page web comprenant le produit, et le serveur d'analyse envoie le message optimal déterminé, en réponse à la demande.
PCT/GB2014/053791 2013-12-19 2014-12-19 Procédé, serveur, système et produit de programme informatique pour fournir un message WO2015092430A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
GB201322568A GB201322568D0 (en) 2013-12-19 2013-12-19 Taggstar 1
GB1322568.5 2013-12-19
GB201413386A GB201413386D0 (en) 2014-07-29 2014-07-29 Taggstar 2
GB1413386.2 2014-07-29

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107169592A (zh) * 2017-04-24 2017-09-15 北京趣拿软件科技有限公司 提示信息的方法和装置
CN109344392A (zh) * 2018-08-23 2019-02-15 广州市万隆证券咨询顾问有限公司 一种证券客服咨询的智能消息推送方法、系统及装置
CN114969249A (zh) * 2022-04-28 2022-08-30 江苏四象软件有限公司 数据挖掘系统及数据挖掘方法

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Publication number Priority date Publication date Assignee Title
GB2420949B (en) 2003-07-18 2007-05-30 Starhub Ltd Message system

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Publication number Priority date Publication date Assignee Title
GB2420949B (en) 2003-07-18 2007-05-30 Starhub Ltd Message system

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107169592A (zh) * 2017-04-24 2017-09-15 北京趣拿软件科技有限公司 提示信息的方法和装置
CN107169592B (zh) * 2017-04-24 2021-03-23 北京趣拿软件科技有限公司 提示信息的方法和装置
CN109344392A (zh) * 2018-08-23 2019-02-15 广州市万隆证券咨询顾问有限公司 一种证券客服咨询的智能消息推送方法、系统及装置
CN109344392B (zh) * 2018-08-23 2023-02-03 广州市万隆证券咨询顾问有限公司 一种证券客服咨询的智能消息推送方法、系统及装置
CN114969249A (zh) * 2022-04-28 2022-08-30 江苏四象软件有限公司 数据挖掘系统及数据挖掘方法

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