In a data-driven world, for anybody working in wine and culinary tourism, data analytics can be a headache. Data are obviously present in tourism and we should not be complacent about such an important aspect of our businesses. IWINETC speakers Emilio Zunino and Andrea Torassa of Maiora Solutions help us to understand and, more importantly, to experience how data analytics can help us.
At IWINETC 2019 Spain, you talked about how advanced data analytics can boost profit for wine tasting tours and resorts. What do you mean by advanced?
Data analytics methodologies and techniques can be grouped into three categories: descriptive, predictive and prescriptive.
Descriptive analytics allows you to see and quantify what happened in the past. A good example of descriptive analytics techniques and tools is a sales report with visual elements, such as charts and conditionally-formatted tables, showing which country or sales manager contributed the most to past revenue results, at different levels of granularity. This is “simple” analytics because descriptive techniques, methodologies and tools represent acquired information in a more effective way and facilitate the decision-making process, but they do not provide new information.
Advanced analytics concern predictive and prescriptive analytics because they can start from data and information from the past and provide new information and directions, through the application of mathematical and statistical methodologies.
Predictive analytics typically refer to demand forecasting techniques, which allows you to determine future scenarios of sales, price pattern, costs and any other metric applying different techniques (moving average, exponential smoothing, ARIMA, …) to past data. You can then have a set of possible future scenarios, which is new information, upon which take better decisions about your commercial and pricing strategy.
Prescriptive analytics combine past data, forecasting models and optimization techniques to deliver actionable recommendations which can boost economic performance. Optimization techniques are based on mathematical, statistical methodologies and data science methodologies such as non-linear regression, decision trees and machine learning. With prescriptive models you have an AI support to your decision making process, configuring the so-called augmented intelligence approach to work and decisions.
Can you give us an example of the use of advanced data analytics applied to a tour operator or travel agent?
Regarding tourism & leisure operators, such as airlines, hotels, cruises, ferries, trains, etc… We can talk about advanced analytics when we refer to revenue management systems. These are a good example of prescriptive analytics tools, as they provide price and inventory recommendations to maximise revenues, operating margins and occupancy levels. Hence, they are able to give new information and directions from advanced analysis of key elements such as past demand seasonality, customer segmentation, price evolution and elasticity. They incorporate forecasting and optimization models, with which they can estimate future demand variation and impact of economics from the application of recommended price levels.
Tourism & leisure sectors are the ones where data analytics and price optimization techniques had been introduced and developed since the very beginning, because they always presented availability of data (through automatic booking engines) and the perfect conditions for application of revenue management: possibility to vary the price and predictable duration of each service.
Nowadays, data analytics and revenue management can be successfully applied to a booming sector such as restaurants. New technologies like integrated management systems, digital menus and totems, and the evolution of customer behaviors through online booking and aggregators, allow restaurant managers to have an unprecedented availability of data and the capability to apply dynamic menus and prices based on forecasted demand.
have developed a prescriptive system for restaurants which enable advanced
analytics in this industry. The system is based on the concept of augmented
intelligence, which is the successful union of artificial and human
intelligence: the system recommends based on data and statistical algorithms,
the human takes the final decision complementing analytical insights with
experience and business acumen.
Restaurant managers can now interrogate this system to quickly evaluate past performance through visual dashboards, predict future demand and revenues and get data-driven recommendations about menu composition and dynamic prices to maximise revenues, occupancy and operating margin.
GDPR is a pain to many…What benefit can it bring to the marketing of wine tourism?
The GDPR can bring several benefits to the tourism sector.
First of all, it is important to say that every activity must always be directed towards the protection of citizens and their freedoms and in this case towards the protection of privacy and customer rights. Better management of their data means customer loyalty: the customer feels confident in the brand that is GDPR compliant because he knows that his data will be managed correctly in that structure.
Secondly, the GDPR is not just a legal issue but it goes hand in hand with IT security: investing in privacy and GDPR is a way to prevent possible IT security failures and data breaches. This prevents damage, both economic and reputational.
Also, GDPR in the tourism sector implies better process management and data retention. By correctly applying the GDPR, the data processed and stored by tourism facilities are consolidated and accurate (the elimination of obsolete and unnecessary data implies a significant reduction of unnecessary costs and procedures). By facilitating the adoption of processes within the company, productivity is also improved, and this can help foster a better data-analytics culture in the company, which will finally lead to a better customer service and experience.
Finally, being Privacy compliant certainly means greater credibility and consolidation of the position in the market, even towards competitors.
So, yes, it is a pain to many, but we feel it’s a good investment (and it’s mandatory anyway…)
How ready is our industry? Are there any challenges specific to wine and culinary tourism players?
In the wine industry we have a lot of amazing players with a true passion for their products, for quality and for great customer service; this is surely a strong asset in the industry, which will help a fast recovery, even in complicated times like this, when the need of sociality is somehow faltering.
For those who work also in the tourism industry, once we all go back to normal there might even be some business opportunities, thanks to the fact that most players in the industry have a limited size, and therefore there isn’t the overall perception of mass tourism with too much physical contact.
In terms of data-use readiness, instead, what we have noticed so far is that most businesses are quite small, with a strong entrepreneurial spirit and a true passion for the product, but with few weaknesses in terms of pure analytical skills. Overall, an entrepreneur is not a manager, and you don’t need a corporate style organization in a small business, but some of that managerial mindset, with a stronger attention to data would help any company – no matter the size – in getting better results. Sometimes we notice that even companies that have good results could actually have better results if they used a more analytical approach. And in crisis times every Euro matters.
Many businesses in the wine and culinary tourism industry are 1-3 persons tops with little or no time at all to get their heads around the data driven world we are in. What advice would you give to such businesses?
I would suggest to start from the basics: sometimes we might think that the use of data analytics means involving scientists and complex statistical models with a lot of maintenance and time-consuming reporting and tools to be updated every day. This can be scary.
But in fact for small businesses even some simple sales & customer reports with charts and tables might help improve the analytical skills within the company, and might help identify hidden business opportunities. Being a data analytics master is not the purpose of tourism managers, but it is very important to understand what data tell us. First start with descriptive analytics, such as sales & customer reports, then move to predictive analytics, such as forecasting models, and then adopt a price optimization model, based on prescriptive analytics. There are no shortcuts.
The best approach to start with descriptive analytics would be to identify the key measures and indicators that are useful for the business (is it sales? Guests bookings? Average price paid?) and – even with the support of someone more IT-skilled – work on a reporting template that can be easy to read, understand and quick to update. The final goal would be to spend one or two hours a week on updating and reviewing the weekly figures, at the beginning of each week, to help set the working priorities and agenda for the next few days.
Once a company is at ease with this approach, and a data culture starts to grow, then we can consider more advanced steps, like embedding the website data in the weekly analysis, or integrate some CRM concepts, to better understand our customers’ needs, and be more proactive in our sales approach.
We understand that approaching data can be scary at first, but they are literally everywhere, even in simple forms; in our Linkedin page we try to give every week some insights about the use of data in the real world, to share our simple view: data can be scary and overwhelming, but they don’t have to be that way!