The Impact of Digital Marketing Strategies on the Performance of Rural Tourism Unities in Alentejo

Webcare

2.1

Webcare can be defined as the participation of companies in conversations with customers, primarily through responding to reviews, particularly with the aim of mitigating negative reviews, as well as enhancing the effects of positive reviews, in order to improve client attitudes toward the product/company (Casado-Díaz et al., 2020 Le, L.H. and Ha, Q.-A., 2021). This type of digital marketing strategy can be analysed from various perspectives. Response strategies (Casado-Díaz et al., 2020; Sparks et al., 2016; Xie et al., 2017) can be either defensive — attempting to explain the service failure through external factors without taking responsibility for it — or accommodative — where the company admits their fault for the issue. Not responding is also considered an action and can be categorized as a strategy. The voice of response can be formal and standardised (i.e., the same for all types of reviews) or more personal, with an emotional style that addresses the review and the issues raised in it, paraphrasing the reviews (Pelsmacker et al., 2018b; Sparks et al., 2016; Xie et al., 2017). With respect to the job positions of the response providers (Xie et al., 2017), responses can come from the front line (e.g., from a receptionist whose name the customer recognises), or from top management (e.g., from an executive or marketing director). Finally, the timeliness of the response — that is, the time elapsed between the review and the response — is also considered significant (Pelsmacker et al., 2018b; Sparks et al., 2016; Xie et al., 2017).

Several studies have found that webcare can have positive effects on the KPIs of tourism businesses. Pelsmacker et al. (2018b) observed that responding to guest reviews has an indirect effect on OR, leading to an increase in the volume of reviews. In a more recent study, it was observed that responding to negative reviews has a positive impact on valence (Ravichandran & Deng, 2023). Casado-Díaz et al. (2018) found that accommodative responses counteract the harmful effects of negative reviews on customers’ attitudes toward the company. This is in line with the findings of Kapeš, J. et al. (2022), who concluded that a defensive response (like an excuse in which the company recognises the problem but blames a third party) can damage a business’s image. Lopes et al. (2024) found that too many apologies, even when inserted in accommodative responses, can have a negative effect on bookings.

Casado-Díaz et al. (2018) argue that more important than choosing between an accommodative or defensive response is the simple act of responding. Purani and Jeesha (2023) concluded that responding to all reviews increases future customers’ engagement intentions. Lopes et al. (2024) found that even a defensive response has a positive effect on booking intentions compared with no response, because hotels that provide webcare are perceived as giving more importance to customers than hotels that do not respond. Xie et al. (2017) found that a large volume of responses can have a positive effect on the financial performance of tourism businesses. It has also been shown that responses with more personalised discourse, particularly those that paraphrase the review, have beneficial effects on future customers’ booking intentions (Min et al., 2015; Jacobs & Liebrecht, 2023; Jin, W. et al., 2023) and improve RevPar (Palese et al., 2021).

It also seems important for the company to demonstrate through its actions that it takes the customer’s reviews into account (Xie et al., 2017), resolving issues that have led to negative reviews in a definitive manner.

Regarding the job position of the response provider, studies are contradictory, with some pointing out that responses given by staff members have more beneficial effects (Xie et al., 2017), while others suggest that responses from top executives inspire more trust (Sparks et al., 2016; Lopes et al., 2024).

Finally, regarding the timeliness of the response, there are also discrepancies. Some studies suggest that responses should be given within 24 hours, and that the longer a review goes unanswered, the worse the financial impact (Pelsmacker et al., 2018b; Xie et al., 2017; Kumar and Maidullah, 2022). Lopes et al. (2023) emphasise that a timely response is beneficial because it not only increases consumers’ perception of justice and increases trust, but is also beneficial for the future volume and valence of reviews, beneficially influencing financial KPIs. Other studies contend that response speed is not important, as comment/response pairs are not aimed directly at influencing the complaining customer, but rather a future customer who might come across them after a week — or after as much as two years (Litvin & Hoffman, 2012; Min et al., 2015). Based on the results of studies discussed above, we propose the following hypotheses:

H_1a: There is a positive correlation between rural tourism lodgings’ responding to reviews and their KPIs, regardless of the valence of the reviews.

H_1b: There is a positive correlation between rural tourism lodgings’ KPIs and an accommodative response strategy.

H_1c: There is a positive correlation between a personalized, empathetic voice of rural tourism lodgings’ review responses, their paraphrasing of the review, and their KPIs.

H_1d: There is a positive correlation between the KPIs of rural tourism lodgings and their responses presenting solutions to customers’ problems.

H_1e: There is a positive correlation between the KPIs of rural tourism lodgings and responses signed by toplevel employees with an indication of position.

H_1f: There is a positive correlation between rural tourism lodgings’ KPIs and response to reviews within 24 hours.

Visibility

2.2

The other strategy analysed involved the online visibility of tourism ventures. Online visibility can be defined as the ability of a brand to be easily recognized in an internet context. This is achieved in the offline world through advertising in traditional media such as billboards, television, and the like (Smithson et al., 2011). In the online world, brand recognition is built through a massive presence on internet — for example, through banner ads or links that redirect customers to the brand’s website, or through the brand’s presence on social media platforms such as Instagram (Pelsmacker et al., 2018a; Smithson et al., 2011).

Brand visibility can also be increased by leveraging internet users’ search habits (Smithson et al., 2011). When an internet user seeks information about a subject, they use a search engine with keywords. The result of that search generates a list where websites, pages, blogs, etc., appear ranked by relevance, with the pages that most closely match what the user is searching for appearing at the top. The ability of a brand to appear at the top of these lists also provides visibility to the brand (Smithson et al., 2011), and the more a brand appears in the top positions of search result lists, the greater the likelihood that an internet user will choose it over other lower-ranked options.

This type of online visibility strategy is called search engine marketing. These tactics are divided into organic strategies like search engine optimisation, which involves using meta tags on company websites to make it easier for search engines to find the brand’s website when certain keywords are searched, and paid strategies like search engine advertising, which entails buying keywords through services like Google AdWords (Pelsmacker et al., 2018a).

OTA and metasearch websites are used in a similar way to search engines, but are specifically designed for tourism (Angeloni & Rosi, 2021). Here, it is also possible to use visibility strategies to position a tourism venture first in a search list. This can be done through free techniques integrated into search engines’ optimisation strategies, such as uploading higher-quality photographs or improving the rating given by customers, or through paid techniques, such as joining special programmes that involve a payment to the OTA.

Some authors, such as Melo et al. (2017), argue that visibility on an OTA’s platform directly depends on the amount of money paid by the lodging unit to the platform. In the case of Booking.com, this refers either to commissions paid by the lodgings to the OTA, or to joining programmes like the Genius customers programme, where, in exchange for a 10% discount offered to customers by the accommodation, the platform grants access to a specific group of customers who have made a high volume of bookings through the platform during the year (Booking.com, 2020a). There is also the Preferred Partner programme, which encourages accommodations to pay a higher commission (18%) in exchange for better visibility in search results (+ 65% views) (Ivanov & Atanasova, 2019). This programme is exclusive to the top 30% of the highestrated tourism establishments in a particular area and promises a 40% increase in bookings (Booking.com, 2020b).

These strategies (higher commissions and special programmes) allow for greater visibility and a better position in the platform’s search rankings (Siguencia et al., 2018). According to some studies, this visibility leads to an increase in OR and improves financial results (Melo et al., 2017; Nieto et al., 2014; Raguseo et al., 2016).

Nieto et al. (2014) observed that for the OTA Toprural, paying the platform for greater visibility in search results helps increase the number of customer reviews, and this indirectly translates into profit. Thus, these authors conclude that visibility positively affects companies’ profits directly, but also indirectly, through the impact of visibility on the volume of reviews, which in turn impacts profits.

However, not all authors agree that higher visibility improves financial results. Gabelaia and Gabelaia (2025) conclude that although OTA platforms give visibility to hotels and lead to better OR, in the end, the commissions paid to platforms damage the hotels’ profitability, resulting in lower profit margins.

Based on those results, we propose the following study hypotheses:

H_2a: There is a positive correlation between KPIs of rural tourism lodgings and their paying a higher commission on bookings with the goal of increasing visibility.

H_2b: There is a positive correlation between the KPIs of rural tourism lodgings and their joining special programmes, such as Booking.com Genius or Preferred Partners, with the goal of increasing visibility.

H_2c: There is a positive correlation between paid actions that enhance visibility (SEO) and eWoM indicators, which have positive indirect effects on the KPIs of rural tourism lodgings.

Sample characterisation

4.1

Before analysing rural tourism lodgings on Booking.com using netnography, we checked the tourism ventures that were classified under this category in the RNET. At the time of our study, there were 367 rural tourism units registered in the RNET in the Alentejo region; only 107 of those units with pages on Booking.com met the three sample criteria. These were the ones we observed using netnography. After this observation, the rural tourism units were contacted and the questionnaire was sent to them. Probably due to the sensitivity of the financial questions, only a portion of the 49 rural tourism lodgings units replied to the questionnaire. Our final sample is mostly composed of country houses (see Table 3) and rural tourism units with fewer than 10 years of operation, averaging around 16 to 20 accommodation units and few employees — in most cases, not exceeding three.

An average of 183 comments per sample unit were observed. The valence of the comments was quite asymmetric and trended towards the positive. The same was true for the ratings (Table 4).

Webcare

4.2

Contrary to some studies that concluded that responding to reviews (webcare) is always a better strategy than not responding (Xie et al., 2017; Casado-Díaz et al., 2020; Purani and Jeesha, 2023; Lopes et al., 2024), we did not corroborate Hypothesis 1 (Table 5), and did not find any correlation between rural tourism units’ KPIs and the practice of always responding regardless of review valence (see Table 6). This is in line with the conclusions of Palese, B., Piccoli, G. and Lui, T.-W. (2021).

Therefore, we cannot confirm Hypothesis 1b for these two KPIs (Table 5). However, we must mention (with all due reservations) that if we consider a p-value of 0.1, there is a weak negative correlation between the RevPar indicator and an accommodative response (Table 6). In the case of our sample, this suggests that providing many responses where errors are consistently acknowledged may have a negative impact on RevPar. This is in line with the already-referenced conclusions of Lopes et al. (2024), or the conclusions of Ku, C., Chang, Y., and Wang, Y. (2024), who noted that overly explanatory responses to negative reviews were counterproductive.

Regarding the voice of the response, we did not confirm Hypothesis 1C (Table 5), as no differences were found between a personalised response that paraphrases the review, and a standardized response to all the reviews, like other studies (Min et al., 2015; Palese et al., 2021; Jacobs et al., 2023; Jin et al., 2023). Nevertheless, we found that a personalised response, in which a solution is presented for the specific problem raised by the customer, seems to have a positive impact on GR (Table 6), thus confirming Hypothesis 1D (Table 5) for that KPI. This result is in line with Xie et al. (2017), who concluded that simply mentioning the problem is not enough — it is necessary to show in the response that the issue has been solved or is in the process of being resolved.

Considering the time elapsed between the review and the response – Hypothesis 1F (Table 5) — we find do not find the correlation between the timeliness of response and KPIs (Table 6) that was found by Pelsmacker et al. (2018b), Xie et al. (2017), Kumar and Maidullah (2022), or Lopes et al. (2023). Rather, our findings somewhat corroborate the study by Min et al. (2015), which found that response time has no correlation with the KPIs of tourism establishments. According to those authors, this occurs because, in the case of online complaints, the person who is actually influenced by the complaint and the response may see only them immediately after the review has been posted. Conversely, they may delay getting in touch with the accommodation to post the review for as long as a year (Min et al., 2015), meaning the speed of the response is not very important. Moreover, it is worth recalling that, as we noted in section 3 of this article, response time is not visible on Booking.com, as it was on the platforms used in the studies by Pelsmacker et al. (2018a) and Xie et al. (2017), or even the study of Min et al. (2015), where the authors used a simulation of a platform that disclosed the response date. We instead opted to ask managers the typical amount of time that they took to answer a review from a former customer.

Unlike Casado-Díaz et al. (2020), or Jacob and Liebracht (2023), we did not find any significant correlation, either positive or negative, between the KPIs, OR and GR, and the strategies of accommodative or defensive response (Table 6).

Regardless of the results, one thing seems important: The particularities of each platform, such as whether or not response dates are available, are crucial in determining the importance of a particular characteristic of a digital marketing strategy — in this case, the time elapsed between a review and its response.

Finally, we also did not corroborate Hypothesis 1E (Table 5), as there was no correlation in the observed group between the job position of the responding provider and the KPIs (Table 6). This means that in our results, it is not important whether the person that responds to the review is a top manager or some other staff member. This is inconsistent with the findings of Xie et al. (2017), Sparks et al. (2016) and Lopes et al. (2024). However, should be noted that if the significance level of p < 0.1 is considered, there is a positive (albeit very weak) correlation between signing the response (regardless of the responder’s job position) and the KPI GR (Table 6). This could mean that is important for customers to know who is behind responses given by rural tourism units, regardless of their job position.

Visibility

4.3

Regarding digital marketing strategies for improving online visibility, although there are free ways to improve visibility on OTA platforms, we decided to study three tools on Booking.com that involve a financial transaction — either higher commission payments to the platform (the Preferred Partners programme and the Booking.com Visibility Booster tool) or discounts offered to the customer (the Genius programme) — in exchange for an improvement of the ranking position on that platform.

We found that Hypothesis 2a (Table 7) is confirmed for GR, with a correlation between the payment of a higher commission and that KPI (Table 8).

If we consider p < 0.1, we can also consider the existence of a significant correlation between the payment of a higher commission and RevPar (Table 8).

Regarding participation in special programmes promoted by platforms (Hypothesis 2b, Table 7), there was a significant correlation between joining the Preferred Partners programme and GR, but only if we consider p < 0.1 (Table 8). There was no correlation between the Preferred Partners programme and RevPAR or OR. Similarly, no correlation was observed between the Genius programme and the KPIs analysed (Table 8). Knowing that GR and profit are not the same KPI, these findings go some way in confirming results of Melo et al. (2017), Nieto et al. (2014), and Raguseo et al. (2016), that indicated that higher visibility increases profits. On other hand, it contradicts the findings of Gabelaia and Gabelaia (2025).

However, this positive correlation with financial KPIs was not observed with all the tools analysed in this study. We did not confirm the results of studies that state that greater visibility leads to higher OR (Melo et al, 2017; Gabelaia and Gabelaia, 2025). Finally, we must note that the two tools that show a positive correlation with financial KPIs are those that directly increase the percentage paid to the platform. The tool that offers the customer a discount on the stay showed no correlation among the 49 TER analysed. This is aligns with the assertion of Melo et al. (2017) that visibility on OTAs is directly linked to higher payments to the platforms.

Finally, regarding indirect effects on KPIs through a positive correlation between digital marketing tools that increase visibility and eWoM indicators, as postulated in Hypothesis 2c (Table 9), we found that increasing the commission value or joining the Preferred Partners programme had a positive correlation with the volume of comments. In the case of the correlation with the Preferred Partners programme, it is a moderate correlation, with p < 0.01 (Table 10).

When we examine the relationship between the volume of comments and the KPIs, we observe a moderate positive correlation with GR. Thus, for our sample, we can confirm the conclusions of Nieto et al. (2014) that investment in visibility strategies has a direct effect on financial performance (specifically on GR), but it also has an indirect effect on that KPI through the increase in the volume of comments.

It is also worth mentioning that, although the correlation is weak and only statistically significant if we consider p > 0.1, the Genius programme, which increases visibility, appears to have a negative correlation with rating (Table 10), contrary to the results of Melo et al. (2017). This conclusion deserves some attention, as our study found that rating has a positive correlation with OR, meaning that the Genius programme might negatively influence OR through the mediating effect of rating.