A deep dive into KPIs & analytical use cases for the hotel industry

Reading Time: 12 minutes

Introduction: The customer +hotel perspective

The hotel Industry is a subset of the hospitality Industry that deals with accommodation and related services for traveling consumers. This industry is majorly dependent on tourism and travel. The global hotels and resorts industry took a huge hit in its steady growth rate owing to the COVID pandemic and its related suspension and limitations on international travel, and consequently saw a revenue decline of 44.3%*[1]. The appetite for travel has increased ever since 2022, as travel limitations were lifted. Thanks to a phenomenon of revenge spending- revenge travel and revenge tourism in this case – people have been re-planning and executing their long-canceled travel plans.

With increasing revenues, hotels are actively looking to ensure growth in market share to capitalize on the thriving travel trends. While the hotel industry is already using data and analytics to track key performance metrics relevant to the industry, there is a need to up the game owing to these 2 critical areas:

  1. The emerging trends in AI, where enterprises across industries are attempting to use AI in aiding their business. The smarter businesses using AI get an upper hand in understanding the market and business trends, and hence can strategize accordingly.
  2. The expanding revenue streams of the hotel industry will leave the cash crunched and idea crunched businesses way behind others that are going out of their way to ensure, not just customer satisfaction, but a “WOW customer experience”.

This ranges from global F&B, casinos, spas, sporting events, concerts, parties and events, tie ups with tourism and travel players such as agencies and airlines, OTAs, etc.

Both these areas allow us to ponder the fact that the success of a business is highly dependent on analytics and an out-of-the-box business strategy. Business decisions cannot just be taken from static BI reports and the experience of key stakeholders. It requires something more.

The constantly dynamic nature of hotels

Hotels chains have huge responsibilities on their shoulders. They are constantly re-envisioning their offerings to customers. One bad review from a city’s hotel can lead to a blackmark on the entire chain. Consistency in quality, spread of offerings, loyalty management, and standards maintenance become core to their business, which can be either a boon or a bane.

There is sore competition from not only the regionally successful hotels, but also from bed and breakfasts that provide a home-like environment for travelers.

Keeping the 2 critical areas in mind, how can hotel chains expand their view beyond standard KPIs? What can they focus their in-depth analysis on, to stay ahead of the curve? Before the fresh perspective, let us quickly revisit standard but important KPIs and use cases.

The usual, but of great significance

The hotel industry operates within a complex ecosystem where understanding and leveraging key performance indicators (KPIs) is crucial for success. Standard but important KPIs such as occupancy rate, average daily rate (ADR), and revenue per available room (RevPAR) provide valuable insights into a hotel’s financial health and operational efficiency. By analyzing these metrics, hotels can fine-tune their business models and optimize performance. Let’s discuss the fundamental business models in the hotel industry, the essential KPIs that drive decision-making, and significant use cases that illustrate how these metrics are tracked and utilized today.

Business models in the hotel industry

There are multiple business models that hotels engage. They depend on the following parameters.

  1. Branding of the hotel
  2. Branding standards
  3. Risk/reward profile
  4. Decisions on daily hotel operations
  5. Ownership of property/ site

Let’s understand these parameters in detail. Typically, a hotel business is called a hotel group or chain when it has multiple hotels across regions. The branding of a chain of hotels across regions could be the same or different. For e.g., the IHCL group is the largest hotel chain in India (part of the Tata Group). The IHCL group has both the Taj brand as well as the Ginger brand under their umbrella, and each brand offers a different experience catering to varied guest personas.

In some cases, group companies like these might or might not own the real estate where the hotel is operated. This decides whether the hotel group’s business has an asset light strategy. The hotel management could decide to have 2 different types of contracts: Franchise and management agreements.

In a management agreement, the real estate owner oversees the management’s performance while the hotel management handles the day-to-day operations with the help of an appointed property manager. In this case, management receives a prescribed percentage of revenue and profit as their management fees.

In a franchise agreement, the brand, technology, and operating standards are set by the management and receives a franchise fee from the owner. In this case, the hotel owner runs the day-to-day operations in compliance with brand guidelines.

In a leased hotel, the owner engages in long term agreement with the property owner. This owner could still be in another agreement as management or franchise model.

Sometimes, a few rooms/ floor/ portions of a hotel property could be leased out separately which will be managed by the buyer. These are called strata-title hotels.

Now whatever may be the business model, hotels themselves are of various types.

  • Full-Service Hotels
  • Boutique Hotels
  • Chain/ group hotels
  • Resorts
  • Business hotels
  • Budget hotels
  • Luxury Hotels
  • Airport hotels
  • Motels
  • Bed and Breakfasts
  • Floatels (e.g., House boats)& Rotels (Hotels on wheels)

Image 1a: Rotels
Image 1b: Floatels, Courtesy: Chevalier Floatels
Each of these types are distinguished by a few factors:

  • Star rating
  • Level of services
  • Ownership
  • Guest personas and segments
  • Number of rooms / size of business
  • Stay duration
  • Location based offerings and activities
  • Other facilities

Hotel KPIs

I would broadly categorize relevant KPIs for the hotel industry into 4 categories.

  • Operational KPIs
  • Guest experience KPIs
  • Performance KPIs
  • Financial KPIs

Operational KPIs

KPIs that measure or track working costs have been categorized as operational KPIs. These typically measure anything happening at the backend of the business. Here are some metrics that are important for the industry in discussion.

  • ESG score- A score that measures multiple factors such as lower pollution, lower CO2 output, and reduced waste.
  • Energy consumption- There is significant impact on ROI by optimizing energy consumption using smart energy management systems that use complex ML models across multiple parameters.
  • Water consumption- Measure and analyze water consumption to become sustainable
  • Employee performance: standard performance models

Guest experience KPIs

These KPIs focus on evaluating and improving customer satisfaction and overall experience. They are essential for understanding and enhancing how guests perceive and interact with the business.

  • Online ratings: Sourced from various reviews and booking sites.
  • Online reputation score: This rating is based on essential elements that affect your brand’s strengths and shortcomings.
  • Online reviews: Businesses can analyze online reviews and understand what customers feel about the brand and its facilities.
  • Loyalty performance: Loyalty performance can be managed based on enrolment rates, program engagement rates, redemption rates, etc.
  • CSAT (Customer satisfaction): CSAT is a measure of customer satisfaction collected through anonymous surveys and scored from 0% to 100%.

Performance KPIs

Performance KPIs encompass those that determine where a business stands according to its industry. These KPIs measure the efficiency and effectiveness of business operations. They help in identifying areas of improvement and ensuring that the business meets its operational goals.

  • TAR: Total available rooms.
  • ADR: Average Daily Rate[Rooms Revenue / Occupied Rooms].
  • ARR: Avg. room rate [Total Room Revenue (for a period) / Total Rooms].
  • ARI: Avg. rate Index [Hotel’s ADR / Hotel Market ADR].
  • MPI: Market penetration Index [Hotel’s occupancy rate/ Market average occupancy rate].
  • ALOS: Avg. Length of Stay [#avg. number of stay days].

Financial KPIs

These KPIs monitor and analyze the financial health and profitability of the business. They are crucial for making informed financial decisions and maintaining fiscal stability.

Cost metrics

  • CPOR: Cost per Occupied Room [Total rooms departments cost / Number of rooms sold]
  • TCOA: Total Cost of Acquisition [Total sales and marketing expenses / Number of new customers acquired]
  • MCPB: Marketing Cost Per Booking[Total booking amount- distribution costs]
    Revenue metrics
  • RevPAR: Revenue per Available Room [Revenue per room = Avg daily rate * Occupancy (or)Room revenue / # rooms].
  • NRevPAR: Net Revenue per Available Room [(Room revenue – Distribution costs) / Available rooms].
  • TRevPAR: Total Revenue per Available Room[all revenues generated over all departments (such as food, beverage, and spas, etc.)].
  • RevPOR: Revenue per Occupied Room
  • RGI: Revenue Generation Index (aka. RevPAR yield Index) [Hotel’s RevPAR / Hotel market RevPar]
  • Rack rate: It can be defined as the rate for one night’s stay before discounts or premiums.
    Profitability metrics
  • EBITDA: [(Revenue- Expenses) (or) (net income + interest + tax expenses + depreciation + amortization)].
  • GOP: Gross Operating Profit [Gross Operating Revenue – Gross Operating Expenses].
  • GOPPAR: [GOP/ total # of rooms available per year].
  • Marketing ROI: [(Sales revenue- marketing cost)/ marketing cost].

Common use cases

Hotels today use multiple software and tools to run their business. These may be aiding hotels in their daily operations, workforce management, CRM, loyalty programs, and pricing models.

When we say “use cases” or “solutions“ in this article, we talk about the various types of analytical use cases that data scientists and business analysts build, to uncover useful insights about various aspects of the business.
Here, let us look at the common use cases. (These use cases could have varying levels of data science and modeling requirements, and varying business focus areas.)

1. Customer analytics: Within customer analytics multiple business cases have been effective.

  • Customer behavior analysis
  • Customer segmentation: Identify clusters based on behavior, personas, etc
  • Feedback analysis: Can be trends and insights, areas of improvement, NLP-based sentiment analysis

2. Revenue management

  • Dynamic pricing models
  • Seasonality

3. Demand

  • Forecasting bookings

4. Cost analytics

  • Cost optimization models
  • Predicting inventory requirement
  • Predictive maintenance
  • Staff and guest predictions in FnB
  • WFM report – employee analytics

5. Marketing

  • Targeted marketing

6. Competitor analytics

  • Key metrics comparison with competition
  • Pricing comparison analytics

7. Operational analytics

  • Predictive maintenance
  • Staffing analysis
  • Inventory Management
  • Wastage management

The sparsely explored, but extraordinary

Latest business models in the hotel Industry

Eco-friendly hotels:

Eco-friendly hotels focus on sustainability and environmental responsibility, offering accommodations that minimize their ecological footprint. These hotels implement practices such as using renewable energy, sourcing local and organic food, reducing waste, and conserving water. They appeal to environmentally conscious travelers looking to make a positive impact while enjoying their stay.

Examples:

  • Farm stays (see image 1)
  • Hotels operated in an eco-friendly manner

Image 1: A South African farm stay.

Bed and Breakfasts:

The success of Airbnb and similar platforms has led to an increase in Bed and Breakfast establishments, where homeowners rent out properties to guests. This model allows homeowners to generate income while providing personalized hospitality. BnBs often offer unique and homey experiences compared to traditional hotels, attracting tourists who seek a more intimate and local stay.

Examples:

  • Airbnb
  • Vrbo
  • HomeToGo
  • Plum Guide

Staycation hotels:

Staycation hotels cater to guests looking to experience a location by staying for extended periods, often blending work and leisure. These hotels provide amenities and environments conducive to both relaxation and productivity, making them ideal for remote workers, digital nomads, and families seeking a change of scenery without traveling far. The concept gained popularity during the COVID-19 pandemic as people sought safe and convenient vacation alternatives.

Examples:

  • Long-stay accommodations
  • Workcation-friendly hotels (trended during COVID times)

Themed hotels:

Themed hotels offer unique, immersive experiences centered around specific themes, providing guests with memorable stays. Each hotel is designed to transport guests into a different world, whether it’s through decor, activities, or interactions. These hotels often attract niche markets and enthusiasts looking for a distinctive and engaging lodging experience.

Examples:

  • Giraffe Manor (Kenya) (see image 2)
  • Jumbo Stay (Sweden)
  • Book and Bed (Japan) (see image 3)
  • The Curtis Hotel (Colorado)
  • The Roxbury (Upstate New York)
  • Hotel Not Hotel (Rotterdam, the Netherlands)
  • Cartoon Network Hotel (Pennsylvania)

Image 2: Giraffe Manor, Nairobi
Image 3: Book and Bed, Tokyo

Hotels with ancillary revenue streams:

Overview: These hotels focus on additional revenue streams beyond accommodation, such as theme parks, events hosting, casinos, and spas. They provide a wide range of entertainment and leisure activities, making them destinations in their own right. These hotels attract guests looking for a comprehensive vacation experience that includes dining, shopping, recreation, and unique attractions all in one place.

Examples:

  • Circus Circus Hotel: Casino and theme park (Las Vegas)
  • Marina Bay Sands (Singapore)
  • LEGOLAND Windsor Resort Hotel (Berkshire, UK) (see image 5)
  • Paradise Pier Hotel: Disneyland Resort (California)
  • Hotel Universal Port: Universal Studios (Osaka, Japan) (see image 4)

Image 4: Universal Port, Osaka, Japan
Image 5: Hotel Legoland Windsor Hotel, UK

KPIs that will differentiate hotel businesses

We need to understand that KPIs could have an effect from indirect revenue attribution as well. Placement of hotels near airports, tourist spots, etc., cause the demand of these hotels to depend on “nearby attractions”.
Analyzing the standard KPIs in such cases is not sufficient. Focus needs to be on handling other revenue streams during the off-season such as events, corporate tie-ups, training locations, etc.

Hence two things can happen:

  1. KPIs of other industries become relevant depending on what replacement activities happen in the accommodation premises during non-peak days.
  2. Some standard KPIs of the industry become inapplicable.

Other unexplored use cases in the hotel industry

  • Influencer Analytics: Analyze the effectiveness of influencers in the travel industry. With the influencer industry booming, audiences now trust realistic reviews from general people over celebrities. Determine how hotels can choose the most relevant influencers and derive value from them.
  • Group Hotel KPIs: Compare KPIs across each region for group hotels. This helps in understanding what improvements are required within the current business model to enhance overall performance.
  • Feature Comparison: Compare features across hotels within the same segment and other segments based on star ratings. This helps in identifying competitive advantages and areas for improvement.
  • Hotel Performance Comparison: Evaluate hotel performance across various categories such as resorts, BnBs, and traditional hotels. This comparison provides insights into strengths and weaknesses within different types of accommodations.
  • Price Comparisons: Analyze prices across different hotel categories. Predict the next best alternative hotels for potential customers and ensure competitiveness in pricing strategies.
  • Loyalty Program Analytics: Evaluate the effectiveness of various loyalty program initiatives before investing. Simulations to measure potential success can minimize losses and avoid failed marketing strategies.
  • Customer Sentiment Analysis: Assess customer sentiment across regions within a hotel chain. This analysis helps in understanding guest experiences and improving service quality.
  • Employee-Revenue Correlation: Analyze the correlation between employee performance and revenue for roles such as general managers and VPs. This helps in optimizing workforce efficiency and revenue generation.
  • Rack Rate Analytics: Evaluate and adjust rack rates, which are benchmarks for revenue management and pricing models. Determine if a hotel’s rack rate needs tweaking to optimize profitability.
  • Revenue Stream Analytics: Identify and measure KPIs for various revenue streams apart from room bookings, such as restaurants, casinos, travel experiences, room services, and spas. This helps in maximizing overall ROI.
  • Revenue Channel Analytics: Measure the share of revenue from various channels, including the hotel’s own website, OTAs, partner concerns, marketing channels, and social media. This analysis aids in optimizing revenue distribution.
  • Partnership Analytics: Analyze the effectiveness of partnerships with other businesses, such as travel partnerships with hotels, car hire services, and tourism boards. This helps in making proactive decisions based on demand and maximizing profitability.
  • Vendor Analytics: Evaluate the impact of each vendor on cost and revenue. Compare alternative vendors and determine how they will affect business KPIs to optimize supplier relationships.
  • Event Analytics: Measure the impact of hosting various events, such as corporate events and gatherings, on core room booking revenues. This helps in planning and optimizing event-related income.
  • Theme Analytics: Analyze the cost and impact of maintaining and upgrading themes in themed hotels. This includes assessing the influence of trends, positioning analysis, and overall theme sustainability.
  • Strategic Business Expansion: Conduct simulations to analyze how different strategic decisions impact business performance. For example, determine how adding more rooms to a property affects profitability and occupancy rates.
  • Business Model Comparison: Compare the profitability of different business models. Determine if a change in the business model can enable the hotel to expand its revenue and overall profitability.
  • Travel Analytics: Correlate travel trends with hotel business performance. This analysis helps in aligning hotel services with prevailing travel behaviors and preferences.
  • Quality Analytics: Implement operational quality analytics by collecting granular data on activities such as room cleaning duration and tissue replacement rates. This helps in improving service efficiency and guest satisfaction.

Bringing use cases to life

We now have a good understanding about business models in the hotel industry, KPIs that matter, and use cases that are generally tackled vs. use cases that are yet to see their full potential explored. Let us now talk about how we can bring these use cases to life.

The Hotel Industry today has advanced to collect vast data about various aspects of the business, but experience and status quo of the business still guides decision makers. Decision makers are unable to take strategic and tactical decisions based on data. This landscape needs to change, with brands beginning to apply technological advancements such as Gen AI. But this also means that the hotel industry needs to invest in talent with relevant skills. All this could prove to be a costly affair.

Some global hotel chains, on the other hand, have huge, centralized teams building a vast collection of business intelligence reports, each of them consumed by different business heads. These reports do not provide a well-rounded view of the entire business or answer specific questions in the minds of leaders, leading to gut-based decisioning despite investments in technology.

With the already available business acumen, All this boils down to one thing: The hotel Industry needs just the right offering that can aid their data to decision journey, with low investments, and speed to outcome–the right ammunition amidst giants with troves of experience and industry understanding.

Conclusion: the future of the industry

Hotels can effectively manipulate data, build models, and enable applications with a data-led decision layer using the Fosfor Decision Cloud (FDC).The FDC provides two significant capabilities, among many others, that can elevate hotels to a vanguard position.

  1. A completely low-code, no-code UI, enable your existing talent to produce powerful business outcomes with a short, or almost zero learning curve.
  2. A completely AI enabled, cloud-based product where business users can ask business related questions in simple English.
  3. Easy simulations, nudges, signals, watchlists, forecasting and predictions for faster & better decisions.

The Fosfor Decision Cloud is a connected fabric that aids businesses in their data-to-decisions journey, and helps simplify and accelerate the process.

Hotels can bring innumerable ML models to life using simple API setups and view insights on any app suitable to decision-makers. Business owners can now expand their profitability, improve productivity, become GenAI ready, and unify their data-to-decision journey on one single product.

It’s time for hotel businesses to unravel untouched areas of their business and explore decisions with the Fosfor Decision Cloud. Book your demo with Fosfor!

REFERENCES

  1. https://www.ibisworld.com/global/market-research-reports/global-hotels-resorts-industry/#IndustryStatisticsAndTrends
  2. https://hotelcouncilaotearoa.com/wp-content/uploads/2021/07/HCA-Hotel-Basics-Business-Models.pdf
  3. https://www.shcollege.ac.in/wp-content/uploads/Dr.-Radhika-P-C_Types-of-Hotels.pdf

Author

M S Akshaya

Senior Specialist: Consulting: Media, Entertainment & Travel, Tourism & Hospitality

Akshaya has 9+ years of experience in Solutioning, Sales Enablement and GTM strategy for B2B SaaS products. Her expertise in connecting business problems to technical requirements drive superior solutioning concepts and outcomes. She aims at value delivery for clients and focuses on alleviating business problems in enterprises. She brings in a wide spectrum of technical and business knowledge, from Data science to Sales processes, and can devise go-to-market strategies that adeptly positions B2B tech products to success in new markets and new domains.

More on the topic

Read more thought leadership from our team of experts

Broker performance analysis solution: Analyzing broker performance as an insurance carrier

Most, if not all, large insurance and re-insurance carriers today work with brokerage agencies to grow their books and ensure a healthy stream of business. Depending on the carrier size, they might often work with dozens of agencies spread across the globe, each with its own operating processes and ways of working. For broker managers, monitoring agency performance and working with them to target the right lines of business, suitable policies and the right customers can be a nightmare. The need to be able to quickly analyze broker performance and take corrective actions to meet submissions. As such, underwriting targets is critical. Lumin's Decision Intelligence capabilities make this task considerably simpler. Let’s dive in.

Read more

Data-driven signals on Lumin

We are often troubled by incessant notifications that disturb us on social media platforms. They take our attention and focus away, and the amount of time we lose due to these pesky chimers is countless. But what if we had the power to easily define what friends/communities we would like to keep a tab on? What if we could tell social media to notify us only if we had to know? Interestingly enough, decision-makers and data enthusiasts struggle with this problem too.

Read more

Culture of curiosity

Remember when the world wide web forever changed how people satisfy their curiosity? It was a watershed moment for humanity and the ways we communicate, do business, innovate, and uncover new insights.

Read more
We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners. View more
Cookies settings
Accept
Privacy & Cookie policy
Privacy & Cookies policy
Cookie name Active

What is a cookie?

A cookie is a small piece of data that a website asks your browser to store on your computer or mobile device. The cookie allows the website to “remember” your actions or preferences over time. On future visits, this data is then returned to that website to help identify you and your site preferences. Our websites and mobile sites use cookies to give you the best online experience. Most Internet browsers support cookies; however, users can set their browsers to decline certain types of cookies or specific cookies. Further, users can delete cookies at any time.

Why do we use cookies?

We use cookies to learn how you interact with our content and to improve your experience when visiting our website(s). For example, some cookies remember your language or preferences so that you do not have to repeatedly make these choices when you visit one of our websites.

What kind of cookies do we use?

We use the following categories of cookie:

Category 1: Strictly Necessary Cookies

Strictly necessary cookies are those that are essential for our sites to work in the way you have requested. Although many of our sites are open, that is, they do not require registration; we may use strictly necessary cookies to control access to some of our community sites, whitepapers or online events such as webinars; as well as to maintain your session during a single visit. These cookies will need to reset on your browser each time you register or log in to a gated area. If you block these cookies entirely, you may not be able to access gated areas. We may also offer you the choice of a persistent cookie to recognize you as you return to one of our gated sites. If you choose not to use this “remember me” function, you will simply need to log in each time you return.
Cookie Name Domain / Associated Domain / Third-Party Service Description Retention period
__cfduid Cloudflare Cookie associated with sites using CloudFlare, used to speed up page load times 1 Year
lidc linkedin.com his is a Microsoft MSN 1st party cookie that ensures the proper functioning of this website. 1 Day
PHPSESSID ltimindtree.com Cookies named PHPSESSID only contain a reference to a session stored on the web server When the browsing session ends
catAccCookies ltimindtree.com Cookie set by the UK cookie consent plugin to record that you accept the fact that the site uses cookies. 29 Days
AWSELB Used to distribute traffic to the website on several servers in order to optimise response times. 2437 Days
JSESSIONID linkedin.com Preserves users states across page requests. 334,416 Days
checkForPermission bidr.io Determines whether the visitor has accepted the cookie consent box. 1 Day
VISITOR_INFO1_LIVE Tries to estimate users bandwidth on the pages with integrated YouTube videos. 179 Days
.avia-table-1 td:nth-of-type(1):before { content: 'Cookie Name'; } .avia-table-1 td:nth-of-type(2):before { content: 'Domain / Associated Domain / Third-Party Service'; } .avia-table-1 td:nth-of-type(3):before { content: 'Description'; } .avia-table-1 td:nth-of-type(4):before { content: 'Retention period'; }

Category 2: Performance Cookies

Performance cookies, often called analytics cookies, collect data from visitors to our sites on a unique, but anonymous basis. The results are reported to us as aggregate numbers and trends. LTI allows third-parties to set performance cookies. We rely on reports to understand our audiences, and improve how our websites work. We use Google Analytics, a web analytics service provided by Google, Inc. (“Google”), which in turn uses performance cookies. Information generated by the cookies about your use of our website will be transmitted to and stored by Google on servers Worldwide. The IP-address, which your browser conveys within the scope of Google Analytics, will not be associated with any other data held by Google. You may refuse the use of cookies by selecting the appropriate settings on your browser. However, you have to note that if you do this, you may not be able to use the full functionality of our website. You can also opt-out from being tracked by Google Analytics from any future instances, by downloading and installing Google Analytics Opt-out Browser Add-on for your current web browser: https://tools.google.com/dlpage/gaoptout & cookiechoices.org and privacy.google.com/businesses
Cookie Name Domain / Associated Domain / Third-Party Service Description Retention period
_ga ltimindtree.com Used to identify unique users. Registers a unique ID that is used to generate statistical data on how the visitor uses the web site. 2 years
_gid ltimindtree.com This cookie name is asssociated with Google Universal Analytics. This appears to be a new cookie and as of Spring 2017 no information is available from Google. It appears to store and update a unique value for each page visited. 1 day
_gat ltimindtree.com Used by Google Analytics to throttle request rate 1 Day
.avia-table-2 td:nth-of-type(1):before { content: 'Cookie Name'; } .avia-table-2 td:nth-of-type(2):before { content: 'Domain / Associated Domain / Third-Party Service'; } .avia-table-2 td:nth-of-type(3):before { content: 'Description'; } .avia-table-2 td:nth-of-type(4):before { content: 'Retention period'; }

Category 3: Functionality Cookies

We may use site performance cookies to remember your preferences for operational settings on our websites, so as to save you the trouble to reset the preferences every time you visit. For example, the cookie may recognize optimum video streaming speeds, or volume settings, or the order in which you look at comments to a posting on one of our forums. These cookies do not identify you as an individual and we don’t associate the resulting information with a cookie that does.
Cookie Name Domain / Associated Domain / Third-Party Service Description Retention period
lang ads.linkedin.com Set by LinkedIn when a webpage contains an embedded “Follow us” panel. Preference cookies enable a website to remember information that changes the way the website behaves or looks, like your preferred language or the region that you are in. When the browsing session ends
lang linkedin.com In most cases it will likely be used to store language preferences, potentially to serve up content in the stored language. When the browsing session ends
YSC Registers a unique ID to keep statistics of what videos from Youtube the user has seen. 2,488,902 Days
.avia-table-3 td:nth-of-type(1):before { content: 'Cookie Name'; } .avia-table-3 td:nth-of-type(2):before { content: 'Domain / Associated Domain / Third-Party Service'; } .avia-table-3 td:nth-of-type(3):before { content: 'Description'; } .avia-table-3 td:nth-of-type(4):before { content: 'Retention period'; }

Category 4: Social Media Cookies

If you use social media or other third-party credentials to log in to our sites, then that other organization may set a cookie that allows that company to recognize you. The social media organization may use that cookie for its own purposes. The Social Media Organization may also show you ads and content from us when you visit its websites.

Ref links:

LinkedInhttps://www.linkedin.com/legal/privacy-policy Twitterhttps://gdpr.twitter.com/en.html & https://twitter.com/en/privacy & https://help.twitter.com/en/rules-and-policies/twitter-cookies Facebookhttps://www.facebook.com/business/gdpr Also, if you use a social media-sharing button or widget on one of our sites, the social network that created the button will record your action for its own purposes. Please read through each social media organization’s privacy and data protection policy to understand its use of its cookies and the tracking from our sites, and also how to control such cookies and buttons.

Category 5: Targeting/Advertising Cookies

We use tracking and targeting cookies, or ask other companies to do so on our behalf, to send you emails and show you online advertising, which meet your business and professional interests. If you have registered on our websites, we may send you emails, tailored to reflect the interests you have shown during your visits. We ask third-party advertising platforms and technology companies to show you our ads after you leave our sites (retargeting technology). This technology allows us to make our website services more interesting for you. Retargeting cookies are used to record anonymized movement patterns on a website. These patterns are used to tailor banner advertisements to your interests. The data used for retargeting is completely anonymous, and is only used for statistical analysis. No personal data is stored, and the use of the retargeting technology is subject to the applicable statutory data protection regulations. We also work with companies to reach people who have not visited our sites. These companies do not identify you as an individual, instead rely on a variety of other data to show you advertisements, for example, behavior across websites, information about individual devices, and, in some cases, IP addresses. Please refer below table to understand how these third-party websites collect and use information on our behalf and read more about their opt out options.
Cookie Name Domain / Associated Domain / Third-Party Service Description Retention period
BizoID ads.linkedin.com These cookies are used to deliver adverts more relevant to you and your interests 183 days
iuuid demandbase.com Used to measure the performance and optimization of Demandbase data and reporting 2 years
IDE doubleclick.net This cookie carries out information about how the end user uses the website and any advertising that the end user may have seen before visiting the said website. 2,903,481 Days
UserMatchHistory linkedin.com This cookie is used to track visitors so that more relevant ads can be presented based on the visitor’s preferences. 60,345 Days
bcookie linkedin.com This is a Microsoft MSN 1st party cookie for sharing the content of the website via social media. 2 years
__asc ltimindtree.com This cookie is used to collect information on consumer behavior, which is sent to Alexa Analytics. 1 Day
__auc ltimindtree.com This cookie is used to collect information on consumer behavior, which is sent to Alexa Analytics. 1 Year
_gcl_au ltimindtree.com Used by Google AdSense for experimenting with advertisement efficiency across websites using their services. 3 Months
bscookie linkedin.com Used by the social networking service, LinkedIn, for tracking the use of embedded services. 2 years
tempToken app.mirabelsmarketingmanager.com When the browsing session ends
ELOQUA eloqua.com Registers a unique ID that identifies the user’s device upon return visits. Used for auto -populating forms and to validate if a certain contact is registered to an email group . 2 Years
ELQSTATUS eloqua.com Used to auto -populate forms and validate if a given contact has subscribed to an email group. The cookies only set if the user allows tracking . 2 Years
IDE doubleclick.net Used by Google Double Click to register and report the website user’s actions after viewing clicking one of the advertiser’s ads with the purpose of measuring the efficiency of an ad and to present targeted ads to the user. 1 Year
NID google.com Registers a unique ID that identifies a returning user’s device. The ID is used for targeted ads. 6 Months
PREF youtube.com Registers a unique ID that is used by Google to keep statistics of how the visitor uses YouTube videos across different web sites. 8 months
test_cookie doubleclick.net This cookie is set by DoubleClick (which is owned by Google) to determine if the website visitor’s browser supports cookies. 1,073,201 Days
UserMatchHistory linkedin.com Used to track visitors on multiple websites, in order to present relevant advertisement based on the visitor’s preferences. 29 days
VISITOR_INFO1_LIVE youtube.com 179 days
.avia-table-4 td:nth-of-type(1):before { content: 'Cookie Name'; } .avia-table-4 td:nth-of-type(2):before { content: 'Domain / Associated Domain / Third-Party Service'; } .avia-table-4 td:nth-of-type(3):before { content: 'Description'; } .avia-table-4 td:nth-of-type(4):before { content: 'Retention period'; }
Third party companies Purpose Applicable Privacy/Cookie Policy Link
Alexa Show targeted, relevant advertisements https://www.oracle.com/legal/privacy/marketing-cloud-data-cloud-privacy-policy.html To opt out: http://www.bluekai.com/consumers.php#optout
Eloqua Personalized email based interactions https://www.oracle.com/legal/privacy/marketing-cloud-data-cloud-privacy-policy.html To opt out: https://www.oracle.com/marketingcloud/opt-status.html
CrazyEgg CrazyEgg provides visualization of visits to website. https://help.crazyegg.com/article/165-crazy-eggs-gdpr-readiness Opt Out: DAA: https://www.crazyegg.com/opt-out
DemandBase Show targeted, relevant advertisements https://www.demandbase.com/privacy-policy/ Opt out: DAA: http://www.aboutads.info/choices/
LinkedIn Show targeted, relevant advertisements and re-targeted advertisements to visitors of LTI websites https://www.linkedin.com/legal/privacy-policy Opt-out: https://www.linkedin.com/help/linkedin/answer/62931/manage-advertising-preferences
Google Show targeted, relevant advertisements and re-targeted advertisements to visitors of LTI websites https://policies.google.com/privacy Opt Out: https://adssettings.google.com/ NAI: http://optout.networkadvertising.org/ DAA: http://optout.aboutads.info/
Facebook Show targeted, relevant advertisements https://www.facebook.com/privacy/explanation Opt Out: https://www.facebook.com/help/568137493302217
Youtube Show targeted, relevant advertisements. Show embedded videos on LTI websites https://policies.google.com/privacy Opt Out: https://adssettings.google.com/ NAI: http://optout.networkadvertising.org/ DAA: http://optout.aboutads.info/
Twitter Show targeted, relevant advertisements and re-targeted advertisements to visitors of LTI websites https://twitter.com/en/privacy Opt out: https://twitter.com/personalization DAA: http://optout.aboutads.info/
. .avia-table tr {} .avia-table th, .flex_column .avia-table td { color: #343434; padding: 5px !important; border: 1px solid #ddd !important; } .avia-table th {background-color: #addeec;} .avia-table tr:nth-child(odd) td {background-color: #f1f1f1;}
Save settings
Cookies settings