LNER uses live data to only target ads at people when train available at their station

The brief

LNER’s customer base (and revenue source) is mostly discretionary leisure and business travelers. To meet business revenue goals, trains need to depart station at around 80% capacity. This makes LNER’s business model incredibly lean and any spend in advertising needs to be as efficient as possible.

The aim therefor was for MG OMD to bring together live business data and market-leading technology to target people only when there is a train available at their station, to connect users with under-capacity trains and cheaper prices, and also to improve the cost efficiency of PPC spend.

The idea

Live capacity data in MG OMD’s performance optimization strategies would be a game changer for efficiency, but with 52 stations leading to numerous possible journey combinations, it knew it wouldn’t be a simple technology feed that plugged into all our performance campaigns.

Search – as a last touch demand led platform – offered the greatest opportunity for consumer signals, but also made it the most complex channel to activate, with different feeds needed for different search scenarios.

Most users don’t put their full journey specifics into the search bar. Deciding whether to advertise to a user searching ‘London to Edinburgh 3pm train Wednesday 26th January’ would be easy; the feed would signal that there was/wasn’t availability for that train and campaigns could be up-weighted/paused. In reality, however, the large volume of searches are vague in terms of destination, let alone date and time.

So MG OMD decided to launch across the ‘Destination Generic Campaigns’ for broad destination and train related search queries such as ‘train to Newcastle’ and ‘cheap train tickets to London’.

It utilized Airflow orchestration and cloud technologies to ingest LNER’s daily capacity data, from which its logic parsed and statistically analyzed available capacity for every journey over LNERs booking window, categorizing stations and journeys as High, Medium or Low capacity. Once categorized, the technology pushed the appropriate targeting locations into the corresponding campaigns on platform programmatically for activation based on train and journey capacity each day.

In both Google Ads and Microsoft Ads, it mirrored the feed, splitting the campaign into High, Medium and Low campaigns and set up an Auction Time Bidding ROAS bidding strategy in Search Ads 360. Every morning, once the capacity feed determined the availability of tickets at each location, it pushes the data via the Google script and divides the campaigns in platform. The bidding strategy then utilizes AI and machine learning to change the bids in real time and target users that are most likely to convert.

The results

Destination Generics Campaigns in Google Ads and Microsoft Ads from July 1 to September 30 2021 compared to the previous three-month period show that clicks were up 86% (202,523 v 108,870), while CTR improved by 6% and CPC was down by 34%. Sales and revenue also grew.

The capacity feed improved targeting and with users being matched with the right stations and journey CTR went up 6%. Using a bucketing system, it was able to advertise low-capacity trains and cheaper prices which boosted income.

This project was a winner at The Drum Awards for Search 2022. Check out which of The Drum Awards are currently open for entry.