A Data-Driven Approach to Improve the Digital Customer Journey for SMEs
A Case Study On HAILO
In the current, rapidly changing environment, understanding the customer journey and continuously improving the customer experience are key success factors for competing successfully in the online business. A case study of HAILO, a German-based OEM, shows the impact of a data-driven approach and derived activities on providing a customised digital experience in order to be successful in the digital age. This sneak preview article will be published in the upcoming Marketing Review St. Gallen at the end of August.
By Caroline Heins, Daniela Grumbach, Deniz Herkert, Prof. Dr. Wolfgang H. Schulz
Since early in 2020, the German government has taken actions to tackle the COVID-19 pandemic, such as curfews or shutdowns of local stores, which have significantly accelerated the transition towards digital and online-based distribution channels (Hoekstra & Leeflang, 2020). Digital distribution channels have thus become the most popular alternative to in-person shopping (Coppola, 2021). However, not all players have benefited equally from this development in their online sales due to, inter alia, a deficient customer journey. Small and medium-sized enterprises (SME) face multiple challenges in their digital transformation to increase online sales (Adam & Alarifi, 2021; Omar et al., 2020). Processes and structures that have grown over decades turn out to be insufficient in the digital era. To create a real customer experience, suitable, cross-functional concepts as well as a vision with an agile and digital mindset have to be developed (Holmlund et al., 2020; Homburg et al., 2017; Fassnacht & Königsfeld, 2015). Crossfunctionality and collaboration between departments are essential since digital markets are customer-centric and customer journeys need to be consistent throughout all relevant touchpoints of each journey. Actively managed customer relationships, from which enterprises derive insights for changing and optimizing their entire value creation, are clear
competitive advantages (Schellhorn & Adler, 2015). To create a positive and compelling experience, the right data has to be available to analyse and understand the customer needs and derive the expected experience (Zaki, 2019; Earley, 2018; Wedel & Kannan, 2016). Following this rationale, HAILO, a leading original equipment manufacturer (OEM) in the development, production and distribution of ladders and waste collection solutions, is currently implementing a comprehensive customer-centric approach based on cross-functional collaboration through centralised digital leadership and data management. This case study describes the problems that were identified, the measures taken and the lessons learned in the process.
Background on the HAILO Case Study
HAILO, based in Haiger, Germany, is classified as a medium-sized enterprise and part of the well-known “German Mittelstand” operating in the business-to-business (B2B) and business-to-consumer (B2C) sectors. With around 400 employees, the enterprise is organised in three business units: (i) home & business, (ii) professional and (iii) built-in technology. In 2019, HAILO started to implement
their three-phase digital strategy to create a centralised online customer touchpoint (figure 1). The first phase included the migration to one single domain (hailo.de), the establishment of a single relaunched website, and the merger of shop systems as well as databases. Prior to starting the second phase of HAILO’s digital strategy, the following transformation problems were identified:
- Digital mindset: A consistent digital mindset and common understanding had to be created throughout the entire organisation. To foster a common understanding and commitment of employees, a clear and transparent communication concept without buzzwords was introduced. The way forward and key advantages were explained on a business unit level.
- Market disruption: Markets were and are still changing dramatically, with retailers introducing their own brands and products, new domestic and international manufacturers easily accessing digital markets via marketplaces, and customers buying directly from manufacturers, thus turning former partners into competitors in some fields by bypassing retailers. This has opened up a whole new competitive situation between enterprises with significant pressure on recommended retail and market prices in general.
- Data quality: Founded in 1947, HAILO has gone through different phases of data processing, collecting data according to different logics and in different areas of the enterprise. However, in the latest era of digital transformation, with great processing power, almost endless storage capacities, interconnectivity and many other key drivers, a clear data taxonomy and central data management have become one of the most valuable resources for digital growth. These had yet to be introduced at HAILO.
- Changing environment: Nowadays, customers have access to all relevant information on products and services due to digital media. In the B2C market this is not new, but in the B2B sector such information has traditionally not been readily available capacito buyers; instead, a close and personal relationship was necessary (Pandey et al., 2020). With the opportunities digital channels offer, B2B customers make informed decisions. Therefore, HAILO has to maintain and extend a credible online presence for both B2B and B2C markets by managing customer relationships across all channels.
The second phase was adopted to meet online sales growth targets, e.g., by increasing online visibility, improving the online customer experience and conversion rates, and focusing on customer retention. Data management and the establishment of a centralised customer data platform (CDP) turned out to be the major enablers of relevant acquisition- and conversion-related initiatives such as introducing customer relationship management (CRM). This followed the insight that only with a centralised data management is it possible to maintain data quality and a structured data life cycle, secure access, maximise the value of data and ensure that it reaches the right person at the right time (Wallner, 2019). From data analyses to artificial intelligencebased developments, HAILO will now be able to offer customer-oriented innovations and services. The third phase is currently ongoing, partly driven by fast improvements during the COVID-19 pandemic. HAILO aims to roll out the current setup outside Germany and Austria as well as develop new business opportunities enabled by the new data-driven approach.
Key Pillars of the HAILO Customer Journey
Enterprises, and especially SMEs, are facing human and financial resource constraints (Adam & Alarifi, 2021). Hence, transformation processes are often carried out in small but rather quick steps. These activities require the participation of a multitude of people, experts, strategists, and managers to develop customer-centric solutions (Roubelat, 2000). Therefore, HAILO established the HAILO Digital Unit (HDU), a specialised team, as a central division with the goal to generate online sales growth and to create new business opportunities. The team members were carefully selected and comprise internal and external colleagues who combine internal network and long-term experience at HAILO with digital and marketing experience. Following an agile approach, the HDU divided the strategy into three phases, which ensures the quick adoption of learnings generated from the collected data. The three phases and their concomitant milestones also allow for more frequent internal communication on success stories, which is part of the digital mindset and its transparent communication strategy. Throughout the strategy development process, a major concern of the HDU was to optimise the relevant steps of the online marketing funnel (figure 2) by identifying touchpoints and performing in-depth analyses on how customers can best continue their journey with HAILO to avoid churn. Some of the questions asked by the HDU at each stage of the customer journey are described below:
- Awareness: How do we involve users at an early stage? What type of content are people interested in during an early stage? How do we increase search engine optimisation (SEO) visibility for informational searches via search engines? How do we target relevant audiences that might not consider us yet via social media and display ads?
- Interest: How do we keep users involved through customised retargeting campaigns? How do we move users to the next funnel stage by providing relevant and convincing content?
- Consideration: How do we make users understand our unique selling proposition and convince them to decide in our favour without confusing them with too much information? What is the optimum frequency cap for our retargeting campaigns? What is the best transactional SEO approach during the middle stages of the funnel?
- Purchase intent: What types of pay-per-click campaigns do we need to target as many people as possible that are currently considering our products? Do we need recommendation tools or chatbots to help clients make better decisions or answer remaining questions?
- Purchase/Lead: How should the perfect check-out for our customers be designed? What are the transactional customer needs that we face (e.g. what types of payments and invoices do they require)? How do we reduce checkout abandonment rates and how do we regain customers who dropped out of the process via intelligent e-mail marketing?
- Upselling: What can we learn from our customers’ purchasing behaviour and history? Are there upselling opportunities within or between certain product categories or business units? How do we get in touch with our customers for upselling purposes without annoying them?
- Repeated purchase: In which time intervals do customers check out with a second or third cart? Are there certain patterns that we can use to predict purchases and therefore run predictive email marketing campaigns? What are the main behavioural cohorts that have an above-average retention rate? How can we better target these behavioural cohorts to increase customer lifetime value?
In response to the upcoming Google update (Kleinz, 2021) that will put an end to tracking individual users, HAILO has already taken measures to focus on behavioural cohorts instead of individual users. This will be performed by defining a set of events that can generate a clear picture of the aggregated user behaviour using the analytics tool Amplitude. These cohorts can be targeted on a behavioural basis instead of users’ personal attributes. By focusing on behaviour instead of attributes, HAILO takes its online marketing activities one step closer to the customer needs, thereby further optimizing the online marketing funnel.
Key Initiatives since 2019
In the course of its digital strategy, HAILO implemented a variety of initiatives during the past 2.5 years, which are selectively described below:
- One brand – one website: Merging the different websites into a TYPO3 (primarily for content management) and Shopware (primarily for e-commerce) setup increased usability, improved the customer experience and strengthened their brand through higher visibility in search engines (figure 3). Following Kreutzer (2021), the corporate website is now the nucleus of the enterprise’s entire online communication and is also frequently integrated into multi- and omni-channel communication campaigns. The same applies to the online shop, which is the key driver for activating the maximum potential for e-commerce (Kreutzer, 2021).
- Centralised B2B login: In B2B relations it is common for customers to receive customer-specific prices based on pre-defined conditions or based on the seller’s pricing strategies for certain customer types. HAILO has set up a login area for commercial customers which will display customer conditions and will go live in mid-2021. In 2022, the set-up will be extended to all business units to create a cross-functional customer experience and collect more insights on customer behaviour.
- Centralised data management: In e-commerce, data management, especially quality management of product and customer data, and data analyses, especially of marketing data generated from user behaviour, are key success factors (Wedel & Kannan, 2016). A data-driven strategy generated from comprehensive mapping, starting with a data dump from various systems and based on a clear data taxonomy, is indispensable for growing a profitable digital business for HAILO. The strategy’s main goal is to generate insights from the collected data so that all activities can be managed more effectively and efficiently to create high quality output, e.g. better product recommendations, and provide value to the customers (figure 4). In order to better understand customer needs, HAILO particularly focusses on the CDP approach, which acts as a centralised clearinghouse and repository for data from various external and internal systems (Earley, 2018). HAILO analysed clickstream data, for example, in order to understand the customer journey even better. Based on insights generated from data, a detailed customer understanding is developed by the HDU to define HAILO’s upcoming marketing activities. The challenges within this data-driven approach are the velocity of commerce, the number of variables that need to be interpreted and the granularity of responsiveness to customer needs (Holmlund et al., 2020; Earley, 2018). Every technology and tool in the digital ecosystem produces data streams that need to be analysed and interpreted. In this context, key challenges are (i) identifying which data is important, (ii) understanding what it reveals, and (iii) determining what to do with it. The HDU constantly challenges the status quo to keep focused on the purpose of collecting and analysing data which might change over time (Holmlund et al., 2020; Earley, 2018).
- Funnel optimisation: The most relevant activities to optimise various touchpoints throughout the online marketing funnel were performed in a multi-stage process. It should be emphasised that a consistent data-driven approach was used. The activities were carried out on the basis of data analyses and constantly optimised:
- SEO: HAILO conducted a comprehensive keyword research and derived a demand-focused information architecture for the website, also including early-stage funnel topics, e.g. recommendations on building treehouses or recycling topics. This task was not performed by marketing specialists but rather by data and architecture experts that designed a structure for longterm SEO performance. The investment doubled online visibility within the first two months following the relaunch, which led to a significant increase in website traffic and online shop sales.
- Pay-per-click (PPC) campaign optimisation: For every stage of the funnel, the HDU implemented a standardised approach of continuous campaign opt imisat ion through A/B testing (e.g. variations in ad creatives, page content, user experience) rather than continuous campaign planning with constantly more campaign concepts as is usual in the offline world. This approach led to a significant increase in return on advertising spend from around 200 percent to around 500 percent and in limited cases even to 1,100 percent within the first six months after the campaigns were recalibrated. This means that the campaigns are more aligned to the relevant customer journeys since customers are now clicking on ads at a lower price, follow through the entire funnel at lower costs, and have a higher check-out value. HAILO PPC campaigns are multichannel campaigns ranging from compaid social media content using Facebook and Instagram to search engine advertising (SEA) and Google display ads.
- Organic social boosts and influencer collaboration: The use of social media leads to increased web traffic (Dolega et al., 2021) and is consequently identified as an additional customer touchpoint. HAILO uses Facebook, Instagram and LinkedIn as social media platforms for different target groups. In addition to the PPC campaigns, organic social postings to the news feed are boosted to keep the relevant audiences aware of the HAILO storylines and create an early-stage interaction. By using this approach, HAILO could increase its social media reach year-onyear from 150,000 unique users in 2019 to 2,100,000 unique users in 2021 (1,400 percent) with ad impressions increasing from 190,000 to 7,800,000 (4,100 percent) in the same period. In addition, HAILO recently started a collaboration with an influencer broker who identifies relevant influencers even with small communities to increase conversion rates by reaching out to more relevant audiences.
- E-mail marketing and marketing automation: By analysing customer interactions and key conversion events, the HDU could identify relevant content and important touchpoints throughout the entire customer journey. Based on the conducted analyses, the HDU set up different e-mai l market ing campaigns tailored to the different journeys, as well as marketing automations based on pre-defined trigger events at certain touchpoints. Since this part of the optimisation process has started only recently, no reliable results can be presented yet. It can, however, be stated that this has already led to a more efficient use of internal resources.
- Outbound B2B sales: Since B2B direct sales has been identified as a distribution channel with significant potential, customer data had to be collected for some customer segments first. This was done by a website optin, a lead campaign, and a GDPRcompliant data collection approach. The newly added data was checked regarding duplicates and GDPR compliance. Moreover, a required blacklisting approach was implemented. Outbound campaigns were drafted and implemented into the CRM and the outbound B2B sales campaign was started. The campaign started in May 2021 and is still ongoing.
Key Takeaways and Outlook
HAILO has taken a data-driven and cross-functional approach to its entire digital marketing. Although required investments and internal resources were significant, the return is positive and above expectations. The online revenue increased by 161 percent from 2019 to 2020. Financial results for the first quarter of 2021 reflect further growth. Overall, HAILO’s data-driven marketing puts data taxonomy, data quality, and centralised data management first and makes decision-making and marketing optimisation measurable and objective. The data-driven approach overcomes the limitat ions imposed by fragmented point solutions and presents a holistic approach to customer interactions. HAILO truly puts customers first, provides an appealing customer experience and focuses on customer behaviour based on aggregate and comprehensive data rather than personal observations. This approach generates valuable insights which might have a knock-on effect on all other initiatives, and – based on current reporting – will most likely pay off via revenue and profit migration in the future as well. The COVID-19 pandemic can be seen as an additional driver for increased attention on digital channels. However, this was not the main driver for HAILO’s growth in this distribution channel. The key success factor was the development of a centralised digital leadership and data management concept with all the activities described above. Digital markets also have boundaries, and the more enterprises optimise their activities, the more complex and difficult competition becomes. Once a new equilibrium is reached, a competitive edge can primarily be generated through insights or digital relations that are not available to competitors. This transformation requires a new mindset, new structures, and new processes, which is especially challenging for SMEs that were founded in a primarily non-digital age. From this perspective and to a certain extent, introducing a centralised data management process becomes an enterprise-wide change management process.
- Adam, N.A. & Alarifi, G. (2021). Innovation practices for survival of small and medium enterprises (SMEs) in the COVID-19 times: the role of external support. Journal of Innovation and Entrepreneurship, 10(15). https://doi.org/10.1186/s13731-021-00156-6
- Coppola, D. (2021). E-commerce worldwide – Statistics & Facts. Statista. https://www.statista.com/topics/871/online-shopping
- Dolega, L., Rowe, F. & Branagan, E. (2021). Going digital? The impact of social media marketing on retail website traffic, orders and sales. Journal of Retailing and Consumer Services, 60(5), 1-11.
- Earley, S. (2018). The Role of a Customer Data Platform. IT Professional, 20(1), 69-76.
- Fassnacht, N. & Königsfeld, J. A. (2015). Sales Promotion Management in Retailing: Tasks, Benchmarks, and Future Trends. Marketing Review St. Gallen, 32, 67-77.
- Hoekstra, J. C. & Leeflang, P. S. H. (2020). Marketing in the era of COVID-19. Italian Journal of Marketing, 249–260. https://doi.org/10.1007/s43039-020-00016-3
- Holmlund, M., Van Vaerenbergh, Y., Ciuchita, R., Ravald, A., Sarantopoulos, P., Villarroel Ordenes, F. & Zaki, M. (2020). Customer experience management in the age of big data analytics: A strategic framework. Journal of Business Research, 116, 356-365.
- Homburg, C., Jozić, D. & Kuehnl, C. (2017). Customer experience management: toward implementing an evolving marketing concept. Journal of the Academy of Marketing Science, 45(3), 377-401.
- Kleinz, T. (2021). Keine lästigen Cookies mehr. Zeit Online. https://www.zeit.de/digital/datenschutz/2021-03/google-cookies-tracking-werbung-abschaffen-internet?utm_referrer=https%3A%2F%2Fwww.google.com%2F
- Kreutzer R. T. (2018). Kennzeichnung, Erfolgsfaktoren und Ziele des Online-Marketings. In: R. T. Kreutzer (eds), Praxisorientiertes Online-Marketing. Springer Gabler, Wiesbaden.
- Omar, A. R. C., Ishak, S., & Jusoh, M. A. (2020). The impact of Covid-19 movement control order on SMEs’ businesses and survival strategies. Geografia-Malaysian Journal of Society and Space, 16(2), 90-103.
- Pandey, N., Nayal, P. & Rathore, A. S. (2020). Digital marketing for B2B organizations: structured literature review and future research directions. Journal of Business & Industrial Marketing, 35(7), 1191-1204.
- Roubelat, F. (2000). Scenario Planning as a Networking Process. Technological Forecasting and Social Change. 65(1), 99-112.
- Schellhorn, J. & Adler, B. (2015). Von der Marktbearbeitung zur Customer Experience — Neue Impulse für das moderne Marketing. Marketing Review St. Gallen, 32, 22-27.
- Volz P. & Griep A. (2020). Personalisierung im digitalen Content Marketing. In M. Wesselmann (eds), Content gekonnt. Springer Gabler, Wiesbaden.
- Wallner, M. (2019). Datenmanagement in österreichischen Industrieunternehmen – Umsetzung, Trends und Hindernisse. Montan Universität Leoben. https://pure.unileoben.ac.at/portal/files/4648215/AC15575700.pdf
- Wedel, M., & Kannan, P.K. (2016). Marketing analytics for data-rich environments. Journal of Marketing, 80(6), 97-121.
- Zaki, M. (2019) Digital transformation: Harnessing digital technologies for the next generation of services. Journal of Services Marketing, 33(4), 429-435.