4 Best Practices for Driving Customer Loyalty with Marketing Automation Technology
2017 is poised to be a banner year for travel. The US Travel Association estimates that direct spending by resident and international travelers in the United States is already averaging $2.6 billion a day, or $108.1 million an hour. Global business travel spend hit $1.2 trillion USD in 2015, and it’s on pace to reach $1.6 trillion by 2020, according to the Global Business Travel Association.
Given this substantial growth, it’s critical to acknowledge that the expectations of business and leisure travelers are changing. Because of their daily interactions with highly innovative and disruptive brands like Starbucks, Amazon and Uber, today’s consumers seek personalized, frictionless experiences with on-demand efficiencies at their fingertips and relevant offers presented at the right time and place. The days of static, one-size-fits-all loyalty programs are officially over.
To capitalize on the next few years of record-breaking spending in the travel and hospitality sector, organizations need to re-imagine their customer engagement strategies and differentiate themselves from competitors by delivering unmatched offerings and experiences. Below, SessionM offers four key technologies and best practices to leverage in order to deliver continual, customized experiences and improve customer loyalty:
1. Personalization
Personalization isn’t just a gimmicky marketing tactic; it can drive real revenue. According to McKinsey, personalization technologies can reduce acquisition costs by as much as 50%, lift revenues by 5-15%, and increase the efficiency of marketing spending by 10-30%. Better yet, 75% of travelers are willing to share their personal information in exchange for tailored promotions, coupons, priority service or loyalty points, according to Zebra Technologies.
Between online bookings, customer service and on-site reservation data, most travel and hospitality organizations already have plenty of useful customer data to leverage for personalization technologies, however organizing this endless stream of incoming information can prove difficult. To successfully deliver on a customer’s needs, organizations need to continue to collect customer data from multiple source systems and implement personalization technologies to make that data actionable by combining it into a unified, customer database.
2. Machine Learning
For travel and hospitality organizations, customer relations used to be about following a scripted guide to ensure the best outcome. Now, it’s about big data and analyzing massive datasets to target the best market share and capture the highest possible ROI. Given the scale of data available today, however, it’s simply no longer possible for humans to process this data and respond with an appropriate message in real-time.
Thankfully, machine learning can help organizations gather predictive customer data, detect patterns within large databases and power predictable responses to increase customer engagement and encourage additional reservations, as well as upsell and cross sell services while guests are on-site. For example, with machine learning, a hotel’s system could recognize that when a returning guest checks in at 8 pm, she historically dines at the hotel restaurant between 7-9pm, and usually has a drink with her meal. This information could then trigger a SMS message with a complimentary drink offer, resulting in the guest visiting the hotel restaurant rather than opting to return to her room.
3. Social Media
Organizations using social media solely for advertising purposes are missing out on a huge opportunity to unearth a plethora of data about consumer trends, purchase intent, drivers of sentiment, competitors and category-level conversations. To deliver truly personalized experiences, travel and hospitality organizations need look beyond broad advertising tactics and get to know each customer’s individual tastes and preferences.
Every day, consumers reveal intimate information about themselves, discuss trends and indicate preferences on social media platforms like Instagram, Snapchat, Facebook, Twitter, Pinterest and YouTube. By tapping into this real-time data via technologies that can ingest a steady stream of social data and analytics and tie back social interactions to a single customer’s profile, organizations can build a better map of each of their existing and potential customer’s preferences, and serve their customers as individuals.
4. Productive Partnerships
Most traditional loyalty programs are geared towards rewarding existing or passive behaviors to reduce attrition and leverage an outdated point-per-spend model. Rewards are usually generic and generalized, and offers cannot be tied to specific milestones, behaviors or thresholds.
A more differentiated loyalty strategy, however, can retain and inspire top customers by delivering the right incentive, for the right behavior, via the right channel, at the right time. Partnership programs can further personalize existing loyalty programs, giving customers the ability to earn points when spending at certain partner locations/business. For instance, Hilton and Uber formed a partnership that allows Hilton guests to schedule alerts through the HHonors app to prompt them when they need to arrange a ride via Uber.
To capture a bigger share of imminent 2017 global travel growth, travel and hospitality organizations need to adopt next-generation technology and innovations from some of the most successful consumer brands and reprioritize their marketing stack to deliver consistent, omnichannel experiences throughout a traveler’s entire journey. By embracing personalization technologies, machine learning-powered solutions, social media analytics and mutually beneficial partnerships, organizations of all sizes can better compete with industry leaders, delivering best-in-class customer experiences and driving long-term customer loyalty.