Video Dev News // March 2021

Video Dev News // March 2021

Video Dev News // March 2021

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Findologic Video Dev News // March 2021

Findologic’s first development update of 2021 sees CTO, Georg Sorst explain the latest innovations to our platform. Our development team are continually improving our technologies to ensure that Findologic clients have access to the best solutions on the market.

Our most recent developments include:

    00:20: FINDOLOGIC Li.S.A.

        • An improved user interface, further streamlining the ability for user inspiration based on their preferences (via our A.I. based shopping assistant, Li.S.A.)
        • An improved user interface for Findologic’s express guides, increasing usability
        • The ability to further drill down into search results – Li.S.A. now employs both category refinement and express guides in tandem with one another

    04:16: Improved feature "Support for variants“

        • Support for variants – when a user specifies a particular variant for a product, only exact and relevant specifications and imagery will be displayed
        • Different prices for each variant, size or colour are now possible
        • Consistent images between product listing and product detail page

    06:13: Improved feature "Assisted Suggest“

        • Assisted Suggest now provides even further inspiration to users with immediate product suggestions, and the ability to refine these product suggestions live within the Assisted Suggest box
        • First touch interaction improves the customer experience

     

    Georg Sorst is CTO at FINDOLOGIC GmbH and was the first permanent employee of the company. He helped build both the team and the product from scratch. He gained his IT industry expertise and experience over many years with companies such as IBM as well as various start-ups. As a frequent guest and lecturer at conferences and events he ensures he remains technically up-to-date.  Georg is also a member of the Gesellschaft für Informatik.  What fascinates him about Findologic is the constant challenges posed by the e-commerce market, in particular search technologies with their rapid developments and trends.

    Measuring Pain Point Severity to Prioritise Business Actions

    Measuring Pain Point Severity to Prioritise Business Actions

    Measuring Pain Point Severity to Prioritise Business Actions

    Pain point analysis is essential within eCommerce. It provides a method for assessing the severity of pain points across your website, allowing retailers to prioritise areas for improvement, and understand where their time, resources and budget will have the most impact. Companies investing in their customer journey must be clear about what value particular activities will generate. 

    Common sense suggests to prioritise the issue which impacts the highest amount of people, however, this isn’t always the best approach. Perhaps 100 people are affected by an issue, however, this issue is minor, and will not cause any of those individuals to abandon your website. 

    Meanwhile, 2 people may be experiencing a very severe issue. So severe that they abandon your website and never return.

    Which is more important for your eCommerce team to prioritise?

     

    Define your users, and customer journeys on your online store

    Anybody can identify pain points throughout an online store, however selecting pain points to measure at random, rather than addressing customer journeys one by one, won’t enable any journeys to be fully optimised from start to finish. Instead, retailers should focus on identifying end-to-end customer journeys and optimising the weaker touchpoints. This way, we can focus on streamlining overall customer journeys and ensuring consistency throughout rather than individual pain points.

    To do this, retailers should categorise their users and map out key journeys within these categories, defining important interactions within each journey.

     

    Decide which key metrics you want to measure

    Typically, measuring a pain point considers not just the number of individuals affected by it, but the severity of the pain point. There are a number of data sets an online retailer might harvest in order to measure the severity of a pain point, most notably, impact, reach and task completion time. These metrics are gathered automatically and can be harvested by eCommerce teams via analytical tools.

    However, there are other valuable metrics we can leverage. A more holistic approach utilising a mixture of data sets provides a more comprehensive picture of which aspects of your website require your attention. These data sets require users to provide feedback on the experience and provide insights into a user’s perceived experience rather than the organisation’s assumptions based on user behaviours. These include customer satisfaction, customer effort and net promoter score (NPS).

    A combination of the two data types provides a more comprehensive and accurate picture of a user’s experience with a particular touchpoint. 

     

    Design a scoring system to assess pain-point severity

    The easiest way to define the severity of a pain point is by rating each metric in a pre-defined and consistent manner. Internally, this will require your team to determine scales for each metric and agree upon fixed criteria that will categorise pain points into particular levels of severity upon the scale.

    For example, a typical scale may look something like this:

    • Critical: If we do not fix this, users will not be able to complete the scenario.
    • Serious: Many users will be frustrated if we do not fix this; they may give up.
    • High: There are a few barriers to a user achieving their goal.
    • Moderate: Impacts core journey and users experience reduced performance.
    • Minor: Users are annoyed, but this does not keep them from completing the scenario. This should be revisited later.

     

    Measure

    Let’s compile a list of the data sets we decided to gather earlier and rank each of these metrics on our aforementioned scale, where a score of 1 is a critical issue and a score of 5 is a minor issue:

    1. Impact: score of 4 (moderate)
    2. Reach: score of 1 (impacted upwards of 80% of users)
    3. Task completion time: score of 5 (10 seconds – the quickest 20% of users)
    4. Customer satisfaction: score of 4 (user was satisfied)
    5. Customer effort: scored 5 (minimum effort)
    6. NPS: scored 4 (likely to recommend)

    Medium has generated a formula for calculating the overall pain point severity based on these metrics, however, retailers can create a formula that suits them – the important thing is that is consistent:

    (Impact x Reach x Task completion time) +(Customer satisfaction x Customer effort x NPS)
    Divided by total possible score (250)
    Multiplied by 100 to find the percentage

    (4 x 1 x 5) + (4 x 5 x 5) = 120

    (120 / 250 = 0.48) x 100 = 48

    So, our pain point score is 48!

     

    What does this mean?

    It is important that your team defines their own benchmarks internally to determine pain point thresholds. Typically, this becomes clear over time, as you become more familiar with which scores require immediate action. However, the higher the score, the better that touchpoint is performing.

    As an example, you may decide that any score under 10 needs to be actioned immediately and is earmarked as a high priority. On the other hand, scores over 80 indicate that individuals have a higher tolerance – these will become a lower priority on the corporate agenda. Of course, threshold tolerance depends will vary from business to business.

    Ultimately, this approach ensures quick wins that will have the largest impact. Many companies begin customer-experience efforts with plans to reinvent the wheel, however, one of the single most important things a company can do to achieve a gold-standard CX is link activities to the value they will add. Simply prioritising CX initiatives based on their severity is an important first step in the roadmap to eCommerce excellence.

    Rachel is a Content Marketing Specialist, creating insightful materials on all things eCommerce, tech and Findologic that drive growth and awareness. Rachel has a wide understanding of the tech space, before joining Findologic, she produced content for global FinTech publications as well as working closely with industry leaders for a range of marketing initiatives.

    Findologic appoint Steven Ledgerwood as CRO

    Findologic appoint Steven Ledgerwood as CRO

    Findologic appoint Steven Ledgerwood as CRO

    Findologic, the leading search and navigation platform, has today announced the appointment of Steven Ledgerwood as its new Chief Revenue Officer (CRO). 

    Former EMEA MD of Conductor, a search and content intelligence platform that helps marketers improve visibility online, Ledgerwood joins Findologic with extensive MarTech experience, having held senior executive and board-level roles at Exponea and Emarsys.  

    Having successfully led commercial organisations in the MarTech space for over 15 years across key global markets, including EMEA, APAC and the Americas, Ledgerwood is no stranger to creating and implementing the strategies needed to dramatically accelerate business performance and growth, whether its delivering operational excellence through the creation of new teams or strategising entry into new markets. 

    As CRO, Ledgerwood will spearhead the success of Findologic’s EMEA operations as it eyes ambitious growth plans to solidify its position as the foremost solution provider for global site search and navigation in key markets, including DACH and the UK.  He will be charged with growing the number of retailers and brands who would benefit from Findologic’s solution, including the use of its latest product, Li.S.A.® –®, an AI-based virtual shopping assistant that uses intent signals and discovery to power improved on-site search, whilst expanding the use of Findologic’s capabilities within its existing customer-base. 

    Already working with major European brands, including Carrera Toys, Plumbworld, Lucky Bike, Expert and Pour Moi, Findologic’s 150-strong partner ecosystem – including technology solutions, such as Styla and Nosto, and integrations with global commerce platforms, from SAP and ShopifyPlus to Magento2 and commercetools – perfectly places the business to support brands’ and retailers’ digital transformation journeys as demand for eCommerce continues to boom. 

    Ledgerwood joins at an exciting time for the business, as it announced rapid growth in 2020 and has grown its European team by +25% in the last year.

    „We’re very excited to bring Steve on board,” said Matthias Heimbeck, CEO of Findologic.  “He is a great asset to the team and this move will ensure we can further leverage our strong positioning and innovative services as we expand into new markets and consolidate our leading standing within regions where we already operate.  His profound experience will allow us to scale, setting world-class standards for customer experience as the eCommerce market continues to accelerate at pace.“

    Speaking on his appointment, Ledgerwood commented: “Demand for eCommerce has never been higher, so the imperative is on retail businesses to not only to establish themselves online, but to offer up engaging and straightforward customer experiences that differentiate them from the competition, and keep customers coming back.  Findologic’s solution is uniquely placed to help retailers achieve that; by basing on-site search on intent and not keywords, it revolutionises the way shoppers are served results online, to enhance CX, drive conversions and revenues, all while reducing returns and improving customer lifetime value.”

    Rachel King

    Rachel is a Content Marketing Specialist, creating insightful materials on all things eCommerce, tech and Findologic that drive growth and awareness. Rachel has a wide understanding of the tech space, before joining Findologic, she produced content for global FinTech publications as well as working closely with industry leaders for a range of marketing initiatives.

    Learn from 2020: build resilience within your online store

    Learn from 2020: build resilience within your online store

    Learn from 2020: build resilience within your online store

    Retail is in constant flux – storefronts are shuttered, then reopened and predicting or planning for any long-term goals seems futile. While there will undoubtedly be a shift towards online shopping post-pandemic for example, the return of brick and mortar will bring a downshift to the unprecedented growth we have seen in previous months.

    In just three months, the eCommerce industry achieved 10 years of growth. It is important to recognise that while online stores might see exponential growth, it doesn’t come without its challenges and nothing lasts forever. As the market has grown, so too has competition, shopping behaviours have evolved and expectations have risen.

    What we do know, is that this environment of uncertainty has presented a requirement to both make the most of the current eCommerce boom, but also ensure resilience within your online store post-pandemic, arming your business against volatility and preparing for the new normal. Simply riding the (very lucrative) wave with a short-term orientation isn’t sufficient. When Covid reared its ugly head, it became clear that the crisis will permanently change the way we live our everyday lives, including the way we shop.

    Favoured online shops will be those who re-engineer eCommerce strategies towards tech and behavioural focussed operations, investing in their digital offerings rather than seeing it as an unnecessary expense due to 2019’s eCommerce boom.

    Considered journeys

    Competition and therefore expectations are rising, demographics are changing and demands are evolving. Behaviours have changed and relying on pre-covid customer experiences and touchpoints will impede performance. A number of trends have been identified over the past few months and that should force online retailers to rethink how they serve their customers.

    For example, one of the biggest upticks has been from those aged 65+ – 43% of those in this age group have shopped more online since the start of the crisis. Pre-covid, this age group was the least likely to purchase online due to fears over viruses but have been forced to make the transition. The millions who have made the transition are relatively unsophisticated with online retail and require more supportive and seamless paths to purchase.

    Increased competition in the eCommerce space over since the outbreak of Covid-19 has forced retailers to up their game, as well as bridge the gap between in-person and digital experiences. Taking into consideration the aforementioned points, customers will be more open to new ways of searching, exploring and purchasing products.

    Creating a customer journey that somewhat mimics an in-store experience while taking into consideration new-found demands requires retailers to consider every touchpoint.

    One of the main priorities should be a robust search function. Search is at the epicentre of product discovery and responsible for guiding a user throughout their journey and creating opportunities for upselling and cross-selling. Simply put, if a customer can’t find the product they are looking for, or fail to be met with relevant results they will abandon their search. There are a plethora of on-site amendments that can be made in order to create a powerful search tool, including product recommendations, UX and adaptations to filters. ‘Guidelines to an unrivalled on-site search experience’ details step by step actions retailers can follow to satisfy changing behaviours.

    While A.I. is not yet ubiquitous in the industry, it is a game-changer in bridging the gap between online and in-store. Those that are leveraging the technology hold a distinct advantage with the ability to analyse user data to create more seamless experiences, as well as enhance internal operations. There are many use cases for A.I. across the industry, including a more intelligent search, personalised shopping and inventory management. 

    Tech-centric businesses models

    To survive these unprecedented times, tinkering at the margins of a stagnant, but sustainable business model isn’t sufficient. The best technologies drive higher conversions and overhauls of data and technology processes are critical to develop experiences that lead to a more resilient future.

    Some may see investing in tech as an unnecessary expense due to the rapid growth the industry has seen in recent months, however delivering real-time experiences that bridge the gap between online and in-store requires retailers to rethink stagnant strategies. Internal operations also benefit from tech, allowing the analysis of data to make more informed decisions in uncertain markets. In fact, there are a number of arguments for tech-focussed strategies during these times, including:

    • Consumers can access 1-to-1, personalised support that mimics an in-store experience in real-time, as well as creating the opportunity for upselling and cross-selling
    • Tech helps manage, analyse and predict operational decisions intelligently (such as supply chain management or behavioural analysis) based on large data sets to keep up with unpredictable swings in trends
    • Enable scalable growth through automating operations
    • More control over the everyday management of your online store and additional, smarter features

    Whether building internally or partnering with external providers, tech is vital in driving new revenue streams or increasing current ones as well as driving strategic resilience to ensure competitiveness for a hyper-digital future.

    Data

    Every day, as customers enter your website, large amounts of data are gathered. All too often, retailers fail to harness that data to identify behaviours or process it to provide better experiences. Now more than ever, it is imperative that we do not neglect data. Harvesting data and producing insights is one of the single most important things a business can do to optimise the customer journey and stand out in this ever-evolving ecosystem.

    Improving the speed, quality and scope of data silos is a requisite for any online retailer’s growth. To get the most out of data, a holistic approach is required. When data is managed and evaluated by difference teams, more valuable insights can be drawn.

    Besides the gathering and analysis of data, data can also feed into internal tech and processed in real-time to provide personalised, experiences. During the lockdowns specifically, people have consumed so much content online that brands have been investing in data analytics and insights to execute more relevant experiences. Personalised experiences allow users to feel understood, assisted by the consistently increasing sophistication of artificial intelligence and data analytics.

    The year ahead

    It’s no secret that eCommerce has done well during Covid, but this year, as with any big disruption, businesses will be presented with both obstacles and opportunities. Facing an unpredictable market, every seller should be transitioning towards digital-centric business models and arming themselves with the tools necessary to survive volatility, informed by the lessons learnt this year. 

    Rachel is a Content Marketing Specialist, creating insightful materials on all things eCommerce, tech and Findologic that drive growth and awareness. Rachel has a wide understanding of the tech space, before joining Findologic, she produced content for global FinTech publications as well as working closely with industry leaders on a range of marketing initiatives.

    Welcome to Findologic: Jessica Wilhelm

    Welcome to Findologic: Jessica Wilhelm

    Welcome to Findologic: Jessica Wilhelm

    Jessica joined Findologic’s Munich office as a Sales Consultant in November. Jessica’s responsibilities will revolve around endorsing the Findologic Platform and educating prospective clients on the vast benefits it can provide. We sat down with Jessica to get to know her a little better.

    Q: What was your previous role before joining Findologic, and how did it prepare you for your new role?

    A: Before Findologic, I was Team Lead Sales & Customer Success in a SaaS HR start-up from Munich. I learned a lot, especially with regard to my new role at Findologic, that fun always has a place in customer communication and authenticity always wins anyway. In addition, I learned to stay on the ball and to keep a cool head in uncomfortable and stressful situations.

    Q: Why did you decide to join Findologic and what are you looking forward to the most?

    A: I joined Findologic because I needed a new topic and a new challenge.

    Q: What has been the biggest achievement in your career so far?

    A: To build a functioning team in which motivation was a top priority and I didn’t lose any employee along the way despite the fast pace of today’s working world.

    Q: What is the most innovative thing you have come across recently?

    A: Findologic’s A.I. Platform, Li.S.A.! 

    Q: What’s your secret talent that no one knows about?

    A: I paint and totally lose myself in it.

    Q: What topic could you give a 30-minute presentation on without any preparation?

    A: Attention now – this might get boring. Why digital time tracking, vacation planning and shift planning are an issue that concerns every company.

    Q: If you could meet anyone, living or dead, who would you meet?

    A: Spontaneously, I would say Elon Musk, but he only gives 5-minute slots, and we would need more time for my questions to him – that’s why I choose Michael Jordan due to his mental strength. 

    Gregor is a Digital Marketing Specialist at Findologic. He takes care of inbound lead generation to drive the growth and build awareness around the Findologic Platform.

    HOW TO: Onsite Search – Suchlogik und Unterstützung (4/4)

    HOW TO: Onsite Search – Suchlogik und Unterstützung (4/4)

    HOW TO: Onsite Search – Suchlogik und Unterstützung (4/4)

    Die Onsite Suchfunktion zählt zu den zentralen Funktionen einer E-Commerce Plattform und entspricht dem wichtigsten Sprachkanal zu Ihren Kunden. Hinter der, auf dem ersten Blick manchmal unscheinbaren, Suchfunktion steht nicht nur intelligente Technologie sondern auch eine Vielfalt an Logik- und Design-Entscheidungen, die über Erfolg, bzw. Misserfolg einer Suchfunktion entscheiden. Im Rahmen dieser vierteiligen Artikelreihe möchten wir Ihnen Guidelines und Konzepte an die Hand geben, um auch Ihre Nutzer mit einem genialen Sucherlebnis zu begeistern.

    HOW TO: Onsite Search
    Suchlogik und Unterstützung (Part 4/4)

    Nicht immer ist es möglich die passenden Suchergebnisse zu liefern. Es kann vorkommen, dass der Händler das gewünschte Produkt nicht im Sortiment hat, oder der Intent des Nutzers nicht korrekt erfasst wird. Daher befassen wir uns im abschließenden Teil der Reihe “HOW TO: Onsite Search” mit den Logiken, die im Falle einer leeren Ergebnismenge genutzt werden können, um potenziellen Kunden trotzdem auf der Seite zu halten und Sie im besten Fall zu einem Kaufabschluss zu führen.

    Wichtig zu verstehen ist eingangs, dass ein Großteil der Nutzer nicht direkt bei der ersten Suchanfrage das gewünschte Ergebnis erhalten wird. Der Fokus sollte daher auf einer benutzerfreundlichen Such-Iteration liegen, damit Nutzer auch im Falle einer fehlerhaften Anfrage die nötige Unterstützung erhalten. Dazu zählt die Ausspielung alternativer Suchvorschläge, Fehlerkorrektur und der Umgang mit Suchanfragen, die keine Ergebnisse liefern. Vor allem bei hochrelevanten Suchanfragen gilt es passende Lösungen zu bieten um dem Nutzer eine nahtlose Sucherfahrung zur Verfügung zu stellen.

    1. Offensichtliche Rechtschreibfehler automatisch korrigieren

    Rechtschreibfehler unterlaufen Jedermann. Nehmen wir das Beispiel “T-Shirt”. “Falschschreibweisen” wie “tshirt” oder “Shirt” sollten von Usern nicht als solche empfunden werden.

    Auf mobilen Endgeräten sind Rechtschreibfehler trotz softwareseitiger Unterstützung noch wahrscheinlicher. Den Nutzer im Falle einer fehlerhaften Schreibweise aufzufordern, die Suchanfrage zu verbessern ist ein unnötiger Schritt und führt zu Unzufriedenheit. Vor allem wenn die fehlerhafte Schreibweise zu einer leeren Ergebnismenge und daher auf eine “No-Result”-Seite führt. Des Weiteren könnte es dazu kommen, dass die fehlerhafte Suchanfrage vom Nutzer nicht bemerkt wird und er sich mit den ausgespielten, meist irrelevanten, Ergebnissen beschäftigt und darauf frustriert den Kaufprozess beendet.

    Unabhängig des Anwendungsfalls trägt die Autokorrektur der Suchfunktion maßgeblich zu einer nahtlosen Sucherfahrung bei, da Nutzer ohne zusätzlich zu tätigende Aktion automatisch zum gewünschten Ergebnis geführt werden. Essentiell hierbei ist es jedoch, den Nutzer transparent zu führen, ihn über die Änderung zu informieren und so dem User direkt anzusprechen. 

    Klare Kommunikation der durch die Search-Engine getätigten Anpassungen schaffen Transparenz für den Nutzer

    Wie vorhin bereits erwähnt ist die Fehlerquote auf mobilen Endgeräten aufgrund der begrenzten Größe noch höher. Dementsprechend bietet der Großteil der Geräte bereits Unterstützung in Form von geräteseitiger Autokorrektur, Textvorhersage oder Rechtschreibprüfung. Neben diesen Funktionen kann die Suchfunktion auch zusätzlich durch dargestellte Suchvorschläge oder Autovervollständigung unterstützen, um die Fehlerquote bei mobilen Suchanfragen zu minimieren.

    2. Stellen Sie relevante Inhalte auf der “No-result”-Seite dar

    Nicht immer ist es möglich für jeden Suchbegriff auch passende Ergebnisse darzustellen. Die Gründe dafür sind vielfältig. Sei es ein kryptischer eingegebener Suchbegriff des Nutzers oder fehlerhafte Einstellungen auf Seiten der Suchfunktion. Gerade in Fällen, wo keine Ergebnisse gefunden werden, ist es von hoher Priorität den User nicht im Stich zu lassen, sondern im besten Fall zu überraschen und neue Anreize zu setzen. 

    Wird ihm diese Hilfe nicht geboten, bleiben dem Nutzer nur zwei Möglichkeiten. Er kann entweder den Suchvorgang komplett von vorne starten oder er wird die Seite verlassen. Eine “No-result”-Seite sollte daher in der Implementierung nicht als technische Notwendigkeit gesehen werden, sondern als Help Center, welches den User an die Hand nimmt und ihn zu einer relevanten Lösung führt. 

    Was macht eine gute “No-result”-Seite demnach aus? Was hilft dem Nutzer um zurück auf den richtigen Weg zu kommen?

    Wir haben 6 unterschiedliche Punkte identifiziert, welche sich in mehreren A/B Tests als verkaufsfördernde Elemente herausgestellt haben. Dabei ist es nicht zwingend notwendig alle Punkte zu integrieren, sondern zielgruppenspezifisch die relevantesten Maßnahmen zu identifizieren und kombinieren, um das beste Ergebnis zu erzielen.

    • Alternative Suchvorschläge

    Werden Seitens der Suchfunktion verwandte Suchvorschläge gefunden, sollten diese dem Nutzer auch angeboten werden. Eine Möglichkeit wäre zum Beispiel, die Darstellung des Suchvorschlags in Kombination mit 3-5 enthaltenen Produkten, um den Nutzer einen ersten Eindruck der Ergebnisse zu vermitteln.

    • Personalisierte Empfehlungen

    Produktempfehlungen basierend auf dem bisherigen Browsing- und Einkaufsverhalten des Nutzers, helfen dem User vielleicht nicht zwingend, das gesuchte Produkt zu finden, stellen aber ein wirksames Mittel dar, die Aufmerksamkeit auf andere Inhalte zu lenken, um ihn dadurch auf der Seite zu halten.

    • Kontaktmöglichkeiten zum Kundensupport und weitere hilfreiche Links

    Die meisten Online-Shops bieten heutzutage mehrere Möglichkeiten zur Kontaktaufnahme, wie zum Beispiel durch Telefonsupport oder Livechat. Integrieren Sie die diese Möglichkeiten auf der “No-result”-Seite. Vor allem die Kontaktaufnahme per Livechat wird mittlerweile in Online-Shops gerne und oft genutzt.

    • Kategorievorschläge

    Die Darstellung von Kategorien ist eine gute Option Nutzer wieder zurück in die richtige Spur zu lenken. Idealerweise sollten die vorgeschlagenen Kategorien auch Bezug nehmen auf den eingegebenen Suchbegriff. Sollte das nicht möglich sein, können auch angesagte und beliebte Kategorien eine Möglichkeit bieten, den Nutzer wieder zu möglichst relevanten Produkten zu navigieren.

    • Beliebte Produkte

    Verwandt zu obigem Punkt, wäre die Darstellung von populären Inhalten, wie zum Beispiel der beliebtesten Produkte. Diese Inhalte haben zwar keine Relevanz in Verbindung mit dem Suchbegriff, erinnern den Nutzer aber zumindest daran, auch andere “Top Seller” oder “Best Rated Products” in Erwägung zu ziehen.

    • Externe Anzeigen

    Externe Anzeigen passend zur Suchanfrage können auch ein adäquates Mittel darstellen. Ist die Suchfunktion gut implementiert und unterstützt die meisten Abfragetypen bedeutet eine leere Ergebnismenge mit hoher Wahrscheinlichkeit, dass das gewünschte Produkt im Shop nicht geführt wird. In diesen Fällen kann eine externe Verlinkung in Form kontextbezogener Anzeigen sinnvoll sein.

    3. Berücksichtigen Sie saisonale Produkte

    Einige Shops führen saisonabhängige Produkte, deren Relevanz immer auf einen abgesteckten Zeitraum beschränkt ist, darunter Produkte aus den Kategorien Kleidung, Sport, Dekoration, Geschenke, Blumen oder Lebensmittel. Diese Saisonalität sollte daher auch in den Suchergebnissen berücksichtigt werden. Demnach sollten Produkte die aktuell “Saison haben” höher gerankt werden und umgekehrt Produkte mit geringerer saisonaler Relevanz niedriger ranken. 

    Als Beispiel kann es Sinn machen, im Herbst “Boots” bei der Suche nach “Schuhe” höher zu ranken, da der Verwendungszweck im Jahresturnus wohl höher ist als zB. bei “Zehentrenner” oder “Sneaker”. 

    Die meisten Online-Shops richten ihre Content- und Kategorieseiten nach gegebener Saisonalität aus. Diese Ausrichtung sollte daher auch in der Suche berücksichtigt werden. Dabei sprechen wir aber immer von einer Bevorzugung von saisonalen Produkten. Diese sollte nie so weit gehen, dass andere Produkte ausgeschlossen werden, sondern lediglich später im Suchergebnis erscheinen.

    Sprich: Zeigen Sie, bei gleichbleibender Ergebnismenge, Produkte innerhalb der Listings neu angeordnet in absteigender Relevanz. 

    4. Automatische Weiterleitung bei Suchanfragen zu passenden Kategorien

    Basierend auf den internen Auswertungen, welche im Whitepaper “Kunden wollen finden, nicht suchen” veröffentlicht wurden, ist uns bekannt, dass Nutzer häufig mit einer generischen Suche nach Kategorien oder Marken beginnen. Das Ergebnis ist dabei meist eine unterschiedliche Ergebnismenge, bei Nutzung der Suche im Vergleich zur Navigation über die Kategorie- und Markenseiten. Zusätzlich weisen Kategorie-Seiten zusätzliche Vorteile im Vergleich zur Suchergebnisseite auf, wie etwa bildstarke Content-Welten, klare Navigation durch die Sub-Kategorien, kontextbezogene Produktfilter, Links zu relevanten Inhalten wie Produktführer oder Shopping Guides.  

    In vielen Fällen kann somit als Quick-Win bei einem Match des Suchbegriffs zu einer vorhandenen Kategorie oder Markenseite, direkt auf die jeweilige Landingpage verlinkt werden, um von den genannten Vorteilen Gebrauch zu machen.

    Gregor Sandberger

    Gregor ist der Digital Marketing Specialist bei Findologic. Er sorgt für die Inbound-Leadgenerierung im Marketing um das Wachstum eines einzigartigen Produktes rund um Such- und Navigationstechnologie voranzutreiben.

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