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Microsoft discontinued Bing Travel’s airfare Price Predictor in 2014, not all of Bing Travel. The feature grew out of Farecast, an airfare-forecasting startup founded by Oren Etzioni and acquired by Microsoft in 2008 for a reported $115 million. Its “buy now or wait” idea was distinctive, but maintaining it required extensive fare data, a viable travel product, and sustained investment—advantages Microsoft ultimately did not preserve.
What Farecast promised travelers
Farecast was built around a straightforward question: Should I buy this airline ticket now, or wait? Instead of merely listing available flights, it attempted to forecast whether a particular fare was likely to rise or fall.
The service used historical airfare observations and availability data to turn complex pricing patterns into a simple recommendation. A traveler could see an indication such as “buy now” or “wait,” along with a confidence score. That made Farecast an early, highly legible example of data science applied to an everyday consumer decision.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteFarecast’s prediction technology launched in 2004, according to GeekWire’s historical account. It was founded by Oren Etzioni, then a University of Washington computer-science professor. Etzioni became the product’s most visible public advocate, although the technology was developed and operated by a broader engineering and data-science team.
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Microsoft’s reported $115 million bet
Microsoft acquired Farecast in 2008 and incorporated its technology into Microsoft’s search and travel products. The reported purchase price was $115 million, a figure attributed to GeekWire rather than confirmed by an acquisition filing in the sources available for this account.
The product moved through Microsoft’s Live Search and later became part of Bing Travel. A 2011 Microsoft description identified Bing’s Price Predictor as technology based on Farecast. Microsoft’s strategy was sensible on paper: a useful travel tool could make search more valuable, encourage repeat visits, and differentiate Bing from competing search engines.
Microsoft also added related functions, including flight and hotel search. The prediction feature, however, was the part travelers remembered because it offered a direct decision rather than another list of fares.
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How Bing’s Price Predictor worked
Microsoft’s 2009 explanation provides the clearest public description of the system. At that time, Bing said it had analyzed more than 175 billion airfare observations, using real pricing and availability information. It reported coverage of more than 2,500 origin-and-destination combinations, trips of up to 21 nights, and prediction horizons reaching as far as 180 days.
Those figures describe the product as it operated in 2009. They are historical specifications, not current Microsoft capabilities or a final measure of the system’s lifetime scale.
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At a high level, the workflow was likely:
- Collect fare and availability observations.
- Organize them by routes, travel dates, itinerary characteristics, and time before departure.
- Compare the current fare with historical patterns.
- Estimate the probability of a short-term price movement.
- Show a recommendation and confidence level to the traveler.
Microsoft gave an example prediction with 79% confidence that fares would rise by at least $50 during the following seven days. That was an example of the product’s output—not a claim that Farecast or Bing predicted fares correctly 79% of the time across all routes.
Airfare prediction is inherently uncertain. Airlines can change schedules, remove fare buckets, launch promotions, respond to competitors, or adjust capacity. Weather, local events, fuel prices, and broader economic or political shocks can also invalidate historical patterns.
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On April 8, 2014, GeekWire reported that Microsoft had disabled Bing Travel’s airfare Price Predictor. The important distinction is that Microsoft retired the prediction layer, not every travel function at the same moment.
Microsoft said Bing would continue to provide flight search, hotel search, and travel information through Bing.com/travel, as well as related app and Windows search experiences. Therefore, “Microsoft killed Bing Travel” is too broad a description of what happened. The more precise account is that Microsoft killed the feature that made Bing Travel unusually distinctive: its airfare forecast.
Why did Microsoft shut it down?
Microsoft’s official explanation
Microsoft characterized the decision as a business choice. It said the company wanted to focus resources on travel areas where it saw the greatest opportunities to serve users.
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That explanation leaves out specific financial or operational details, but it reflects the basic economics of the product. A prediction service needs reliable, sufficiently broad data; engineering and travel-industry expertise; consumer distribution; and continual maintenance. If the feature does not materially improve search usage or revenue, it can be difficult to justify those costs.
Etzioni’s explanation
Etzioni was disappointed because Price Predictor had been one of Bing’s most distinctive features. In comments reported by GeekWire, he attributed the decline to several factors:
- Travel-technology and business personnel leaving Bing.
- Google gaining an advantage after acquiring ITA Software.
- Microsoft’s reluctance to pay Google for data needed to power a Farecast-like service.
- Bing Travel becoming a thinner search layer that redirected users to KAYAK.
These were Etzioni’s assessments, not an independently established explanation issued by Microsoft. It would be inaccurate to say simply that Google “killed” Farecast. Microsoft gave a broader resource-allocation rationale, while Farecast’s founder argued that Microsoft failed to capitalize on the product and lost ground in data access and travel technology.
The competitive problem
Farecast’s concept was also becoming less unique. KAYAK had introduced a similar airfare-prediction feature by 2013, according to the 2014 GeekWire report. Once competing travel sites offered comparable guidance, Microsoft had less reason to fund an expensive differentiator unless it could provide better data, distribution, or conversion.
The larger lesson is that a strong algorithm is not enough. Predictive consumer products also depend on sustainable data licensing, dependable distribution, product ownership, and an organization willing to keep improving them.
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Did Farecast’s idea disappear?
No. The original Farecast brand and Bing Price Predictor are gone, but the product category survived. Modern services offer related fare tracking, price-change notifications, or buy-now-or-wait recommendations.
| Service | What it is useful for | Important limitations |
|---|---|---|
| Google Flights | Broad flight comparison, flexible dates, price graphs, route tracking, and notifications about significant price changes or likely increases. | “Cheapest” results can involve self-transfers, different airports, or online travel agencies. Features can vary by route, country, device, and account. |
| KAYAK | Price Alerts, cross-provider comparison, and Price Forecast or Price Trend indicators estimating movement over the next seven days. | Forecasts may not appear when historical data is insufficient. KAYAK is a metasearch engine, not usually the company selling the ticket. |
| Hopper | Mobile-first buy-or-wait predictions, deal alerts, and optional products such as price-freeze or flexible-cancellation offerings. | Predictions are not guaranteed. Optional products may be itinerary-specific, and app-based booking is not ideal for travelers who prefer airline-direct reservations. |
Which Farecast replacement should you use?
Choose Google Flights for research and flexibility
Google Flights is generally the strongest starting point when you want to compare dates, airports, stops, and fare levels. Google allows users to track specific dates, specific flights, or flexible searches such as “any dates.” Its guidance may also indicate that prices are unlikely to drop or are likely to increase.
Google’s notifications are not a promise that a fare will rise, and they may not match the exact “buy now or wait” language Farecast used. Before booking a supposedly cheapest option, check whether it involves a self-transfer, an airport change, separate tickets, or an online travel agency.
Choose KAYAK for alerts and another comparison source
KAYAK combines flight comparison with Price Alerts and, where available, Price Forecast indicators. Its forecasts use historical and real-time information to estimate whether prices may rise or fall over the next seven days.
KAYAK says its predictions are educated guesses and may be unavailable for routes without enough historical data. It also directs users to airlines or online travel agencies to complete bookings, so the traveler should verify the seller, baggage rules, changes, cancellations, and support arrangements.
Choose Hopper for mobile notifications
Hopper is designed around mobile deal discovery and buy-or-wait notifications. Hopper says it analyzes more than one billion real-time flight prices each day and uses historical trends in its predictions. It explicitly warns that predictions are not guaranteed.
Hopper may suit travelers who value app notifications or optional booking protections. It may be a poorer fit if you want a simple desktop research workflow, highly transparent ancillary pricing, or direct booking with the airline.
How to use airfare predictions without overtrusting them
- Set a decision deadline. A “wait” recommendation is not risk-free. The fare can rise, disappear, or become unavailable before the next alert.
- Compare the complete itinerary. Check stops, airports, layover length, baggage, seat fees, and whether the booking uses separate tickets.
- Compare the seller. An online travel agency may show a lower headline price but offer different support or change procedures than the airline.
- Track the exact search where possible. A route-level alert may not represent the same flight, fare class, or baggage allowance.
- Account for your own deadline. If the trip is fixed, the cost of missing the flight or losing a workable schedule may exceed the possible savings from waiting.
- Use more than one signal for expensive trips. Google Flights, KAYAK, or Hopper can help identify trends, but no service can guarantee the future fare.
Why modern predictions can still fail
Forecast quality varies with route popularity, historical data, airline competition, domestic or international travel, date flexibility, itinerary complexity, and whether the system is tracking an exact itinerary or only a general route.
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The lasting lesson of Farecast
Farecast was important because it made predictive analytics understandable. It took massive quantities of pricing data and turned them into a decision a traveler could act on. But its shutdown showed the difference between inventing a compelling feature and sustaining a durable product.
Microsoft acquired a promising airfare-prediction startup, integrated the technology into Bing Travel, and eventually retained ordinary flight and hotel search while removing the distinctive forecast. The reasons remain layered: Microsoft cited resource priorities; Etzioni pointed to organizational departures, Google’s ITA advantage, and data costs; and competitors had begun offering similar functionality.
Today’s Google Flights, KAYAK, and Hopper are functional successors to Farecast’s idea—not direct continuations of its ownership or code. They can help travelers make better-timed decisions, but they remain forecasting tools, not crystal balls. The safest approach is to combine their alerts with a full check of the itinerary, fare rules, seller, and the real cost of waiting.
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