Insurance BANK. Recommended Marketing Measures From Your Onsite Data: Finance. by Spencer Altman Webtrekk GmbH

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1 Insurance BANK Recommended Marketing Measures From Your Onsite Data: Finance by Spencer Altman

2 Words such as trust, service, loyalty and experience often find their way into the communication from financial sector companies. But customer-facing financial websites and apps share a common purpose with their e-commerce, media and travel counterparts: Help the company make money. And web analytics data is essential for doing just that. Some key areas of financial businesses where web analytics can play a pivotal role are: More new customers/accounts Increasing retention/targeting at-risk-for-churn customers Increasing share of wallet Let us look at some examples of marketing tactics that can help digital analytics teams in the financial industry exploit the customer engagement and revenue potential in web analytics data. More new customers/accounts Marketing tactics: Targeted use of exit intent technologies in key signup processes Retargeting and prospecting via native advertising on 1st-party data Retargeting and prospecting via display advertising on 1st-party data Increasing retention/targeting customers at risk for churn Marketing tactics: Customised landing pages for potential churners Net Promoter Score (NPS) for effective targeting of churners We can also discuss here using NPS to increase share of wallet for your loyal customers, which moves into our third area of focus Increasing share of wallet Marketing tactic: Product/service recommendations Targeted use of exit intent technologies Finance 2

3 The integration of various data sources, particularly customer relationship management (CRM) solutions, is critical to boosting the results of these various marketing tactics. Let us now jump into the details. More new customers/accounts Signup forms are critical for companies throughout finance. Common examples include forms for new products, new accounts or contact requests. The reality for financial businesses and their digital analytics teams is that the conversion rate is almost never 100%. Exit intent technologies are an effective, on-thefly, real-time method for decreasing the abandonment of business-critical processes. Exit intent technologies are an effective, on-the-fly, real-time method for decreasing the abandonment of business-critical processes. These technologies display a content layer to users who show their intent to exit by, for example, moving the mouse up towards the tab/menu bar of the internet browser, or being inactive on the page for a certain amount of time. There are various possibilities for the content and context of an exit layer itself. One simple variation for the content of an exit intent layer is simply to inform customers that there is not too much longer until the end of the process: Finance 3

4 Another option is to offer users some customer support such as a link to FAQs, a phone number for customer support or a link to an online chat option: If you have products for which you know customers may need to collect a lot of information prior to moving forward with a signup process, offering further information such as offering a prospectus or industry research, for example can be helpful. A similar tactic may be to offer the customer a free subscription to an industry magazine that your company produces. A benefit here is that if the user accepts your content offer, then you have an additional communication channel open to contact them in the future. Exit Intent with Click here to download text. Offer is Home Magazine or Saving for Retirement. Another marketing tactic to drive customer acquisition activities is using 1 st -party data in both your on-site and display advertising activities. Retargeting and prospecting with the help of your web analytics data can help you target customers more finely and with more appropriate offers. Finance 4

5 Retargeting and prospecting with the help of your web analytics data can help you target customers more finely and with more appropriate offers. Your web analytics data includes valuable information on users who have not yet become your customers. If these users have already been to your site, then you know which products or services they have been searching for. You also know the intensity of their interest in a particular product or service which can be measured in page impressions for a product area, pdf downloads or the number of times a financial calculator/ tool has been used. This information can be used to help determine how much to bid on which users and which products to offer in your retargeting adverts. This advertising can be done offsite in display. The same data can also be used to drive onsite targeting activities for your internal banners to customise the most appropriate banners for the most appropriate customer segments. The data is yours. Put it to work for you. Increasing retention/targeting potential churners Churn is a problem and reality for financial businesses. Customers cancel their accounts and services or decide not to renew them. There are various options for targeting these customers on-site. One option is to customise the homepage or landing pages with a banner for highlighting the benefits of the product you would like them to maintain or renew. A layer can also be used to present this information to this at-risk customer segment. Although identifying customers at-risk for churn may not be a typical responsibility of online teams, the web analytics team can help identify potential churners. This information can then go to the appropriate teams that have additional data on the customers, such as your CRM team and teams that are responsible for determining what to do about these customers and risks. Finance 5

6 A simple, effective and not too aggressive mechanism can be to remind them on the first page of their next visit what their last seen products were. Customers can be identified by the web analytics team as at-risk for churn with various methods: When a customer arrives on your site from a search engine with a search phrase including words similar to cancel or terminate When a user already on your site or app uses internal search phrases similar to cancel or terminate Visits to pages or FAQs whose content is about cancelling an account or service Net Promoter Score (NPS) on the website (we will go into some more detail on this one below ) A process would need to be put in place with the team responsible for dealing with churn, so that this team is aware of which customers have been identified by the online team as being at-risk for churn. This team can also help the online team determine how to more effectively identify potential churners on the website, which may result in, for example, updated FAQs or pages something that will clearly leave an indicator (page seen, clicked link, specific parameter sent) in the web analytics data of churn risk. Net Promoter Score NPS (Net Promoter Score) is a popular way to receive customer feedback in various industries. It can also be used as an effective segmentation criterion in order to help drive your communication with your customers. Finance 6

7 A typical NPS survey looks like this: In the NPS methodology, if a user gives you a ranking of 9 or 10, then they are considered a Promoter of your brand. If they give you an NPS of 6 or lower, then they are considered a Detractor of your brand. The location of the NPS on the website is important. You want to make sure that it is not shown to all visitors, as you do not want to have unnecessary noise in your data from users who are not even your customers. One method to do this is to offer the NPS only in the logged-in section of the website. Another option would be to implement the survey only on the logout page. Both of these measures ensure that only customers are being asked to submit feedback to your company. Your web analytics data then contains information as to which customers are Detractors. Using the processes mentioned above, this information can go to the appropriate group in your company to determine how to deal with these customers. There are some real-time options available to you and your teams for personalising the communication to Detractors immediately upon receiving a Detractor NPS score. Finance 7

8 A banner or overlay can be shown to the user with various personalised content such as: Free subscription to a magazine you produce (for example, on home financing, saving for retirement, etc.) Another dynamic marketing measure to drive sales is to dynamically inform users if products are almost out of stock. Information or special conditions for opening a new account or continuing with an account/product Even at this point, not all Detractors are the same. Customers have different products with you and have different value for your company. For example, a low NPS score from customers with over 1 million euros in various products and a long-term relationship with your institution should likely be handled differently than a low NPS score from a student who just recently started his relationship with your institution by opening an account with a few hundred euros. Even though both groups may have just checked their online banking and given your company a low NPS score, the communication actions taken by your company may need to vary according to the segment. Finance 8

9 Further, which content or which product is communicated also depends on the customer. Again, here an integrated process with your CRM team is extremely helpful, as it would help you determine together which products and services are of potential interest to which customers and customer groups. NPS can also be used to foster loyalty among your Promoters depending on the value that these users have for your company. A segmentation between high-value Promoters and low-value Promoters can be useful. Promoters can be rewarded by offering a free subscription to a magazine you produce or special conditions for opening a new account. Once again, here the integration with CRM can be critical for the success of these actions, as the CRM team would be able to match customer segments to products and services of interest. Determine which users are generating value recently and often, rather than a long time ago and not often. When it comes to determining high-value segments, your CRM/Business Intelligence teams may already have methods in place. In any case, a digital analytics team can use RFM (Recency Frequency Monetary) and/or RFE (Recency Frequency Engagement) segmentation models on the web analytics data to determine not just who is delivering high value, but which users are generating it recently and often, rather than a long time ago and not often. Finance 9

10 To proactively prevent future Detractors, or even identify potential causes of why someone may become a Detractor (not everyone who loves or hates your brand submits a survey), a simple mechanism can be to compare the top pages/products/ services viewed by Detractors with the top pages/products/services seen by Promoters. If there are certain pages/products/services in the list of the Detractors but not for the Promoters, then take a more detailed look at those pages/products/services. A reason for the discontentment may be found there. Increasing share of wallet The signup forms and processes were already discussed in this article. These parts of the website are at the end of a lifecycle funnel. There are other parts of your website which are also important to performance and are earlier in the lifecycle for converting prospects into new customers, or for existing customers who are adding a new account/service. Examples of these pages are the home page and the section overview pages such as an overview page for private banking customers, for home owners, for retirement, etc. which can be personalised in order to increase your share of wallet with customers. These pages can be customised for your users in various ways, such as: Recommendations onsite Exit intent upon leaving With recommendations, you can customise the content shown to users on any page of your site. These recommendations can follow various rules such as: Most popular services/products Last viewed services/products by the current user on the site Recently used calculators or other financial tools The personalisation of these recommendations can be even finer when the model generating these recommendations takes additional data sources into account, such as: Finance 10

11 CRM Data Products/services already purchased/contracted by the customer Demographic information such as age, gender and income Revenue/customer value information Credit rating Existing CRM customer segmentation categories Activity frequency such as trading Offline activities such as branch or call centre activities Much more Web Analytics Data Device type (such as Android v. ios; can also be used as a proxy for income) Campaign source (for example, Facebook v. Twitter v. banner v. search) Search phrase used Much more Available in CRM or Web Analytics Data Geographic information (city, region, country, language preference) Newsletter subscriber Much more There are other data sources which can also be used, like survey data or data from systems. By considering more data, you have a more complete view of the users. As a result, the user experience can be even more personalised with recommendations such as: Most popular services/products only for customers of the same revenue value/level Most popular services/products only for customers who already have the same product/service Most popular services/products only for customers from the same geography Finance 11

12 You can even combine criteria to create more complex rules, which means even more personalised recommendations to engage users and increase your share of wallet with them. Importance of user-centric To be able to get the maximum benefit from the above mentioned tactics, it is important to have a data foundation that is as user-/customer-centric as possible, across all devices and all channels. With a user-centric approach, a single user can be stored and recognised across all of these devices. For at least the onsite data piece (your websites and apps), this means that a customer identifier field should be passed into your web analytics data from the website and apps upon login. Using this identifier is data privacy-compliant, as it does not personally identify a user. This identifier allows you to connect the users activities across multiple devices (from a work laptop to a personal laptop to a tablet to a smartphone). Without a user-centric approach, a single person may be counted in your web analytics data as one visitor per device. With a user-centric approach, a single user can be stored and recognised across all of these devices. Further, the user-centric approach enables you to connect the website and app activities of a user with your CRM data and other data sources for your users, enabling your move to a single view of your users across all of your contact channels with them. Offer your customers a seamless experience across channels from ATMs to a branch to a call centre to their various connected devices (computers, phones, laptops and even TVs). Conclusion The combination of your web analytics data and marketing automation enables a lot of user engagement and revenue generation possibilities for companies in the finance sector. These methods can be made more effective by incorporating other data sources, such as data, CRM data and much more, and enable you to truly personalise the user experience. Finance 12

13 About Webtrekk Webtrekk is a global provider of digital intelligence solutions, headquartered in Berlin with offices in China, Italy, Spain, the Netherlands and the USA. Webtrekk is widely recognised as a leader in digital marketing solutions. Alongside its Digital Intelligence Suite, Webtrekk offers a wide range of consulting services designed to address digital analytics needs, from strategy to implementation to training. About the Author Spencer Altman is Director of Customer Success at Webtrekk. Since joining Webtrekk in 2009, he has been working with companies across the world, with a focus on Europe, to help them get the most out of their digital business. His journey in Digital Analytics began in 2006 as Business / KPI Analyst for weeworld.com, a social network based in the UK. Previously, he spent six years at Accenture in Business Process Consulting in Telecommunications. Spencer has his MBA from HEC Paris and can be reached at spencer.altman@webtrekk.com. Follow Spencer on Twitter. Contact Webtrekk GmbH Robert-Koch-Platz Berlin, Germany Would you like further details and assistance on how to get your company more focused on getting business value from your data? Want to know how Webtrekk can help? Contact us! Send us an at info@webtrekk.com or give us a call at +49 (0) (0) Visit the Website Book your Demo