4 ecommerce challenges solved using analytics

Transcription

1 4 ecommerce challenges solved using analytics

2 4 ecommerce challenges solved using analytics Contents ONE Customer Journey Attribution TWO Valuable Customer Marketing THREE User Flow Analysis (Registration & Purchase) This report will provide you with ways to tackle the four biggest challenges faced by online retail marketers today: multi channel attribution, getting a true view of your customer journeys, integrating your marketing tactics and data and enabling ecommerce sites that convert. As well as outlining the context and implications of getting such data insights right, you can use this report to increase and hone online conversions, and critically, find the information unique to your business to inform smarter, ROI-based marketing decisions. Marketing and analytics professionals can apply these straightforward techniques, using Google Analytics and Google Analytics Premium, to master these ongoing challenges so they can be used as a catalyst for, not barrier to growth. FOUR Targeted Display Marketing

3 Customer Journey Attribution Accurate touchpoint and conversion attribution Understanding all acquisition paths in the conversion funnel is of vital importance. Traditionally, all conversions were attributed using a last-touch model. With the numerous research phases conducted by a typical user, understanding how all marketing channels are working in harmony is now a necessity. Back in 2011, Google conducted a study named the Zero Moment of Truth. Traditionally, the general marketing flow would be as follows: Stimulus > FMOT > SMOT Stimulus Exposure to the brand via an ad, piece of content, word of mouth, etc. FMOT - First Moment of Truth Customer encounters product on shelf SMOT - Second Moment of Truth Customer uses your product, builds loyalty, shares reviews, etc Google then found and defined what is referred to as the Zero Moment of Truth: Stimulus > ZMOT > FMOT > MOT Zero Moment of Truth Moment that occurs after a prospect has been exposed to your brand, but before a purchase is made. This is considered to be the research phase. For marketers, this was found to be the best possible optimisation to push a prospect to a customer as it directly affects the prospects research phase. Continued...

4 Customer Journey Attribution Based on this, Google produced a series of reports and models to assist with determining the acquisition path from stimulus to SMOT in Google Analytics Premium. No longer does Google Analytics attribute to the last touch point that was exposed prior to a conversion taking place. Instead, all acquisition paths are presented in a user friendly way to determine how paths are working in harmony across each moment of truth.

5 Customer Journey Attribution Google Analytics Premium comes with the added benefit of integrating with DoubleClick DoubleClick Campaign Manager (DCM) and DoubleClick Bid Manager (DBM). Therefore, Google Analytics Premium will collect both view-through and click-through display data and feed it directly into attribution models and multi-channel funnels. In addition, Google Analytics Premium comes with a Data-Driven Attribution model. This is algorithmic and determines areas of improvement automatically based on your data. At Jellyfish, we use this consistently to benchmark attribution models and tweak depending on our clients goals, for example, brand awareness, retention, etc: For any ecommerce business, understanding how marketing channels work together is a necessity. We ve reduced marketing spend and simultaneously increased conversions by adopting a simple attribution model. Ref:

6 Valuable Customer Marketing Realizing greater lifetime customer value CRM systems hold a wealth of information. As analytics platforms prevent the collection of personally identifiable information (PII), integrating analytics with your CRM data opens the door to granular customer lifetime analysis. This closes the loop between audience behavior and exact users, demographics and types of customer. To do so, the process involves a few steps: 1. Implement Universal Analytics with multiple Session & User level Custom Dimensions for assigning attributes to a User ID 2. Once a user logs in, encrypt the User ID to match the CRM identifier 3. Upload the unsampled Google Analytics Premium data and the corresponding CRM data into BigQuery 4. Analyze data via SQL or R to determine clusters and trends 5. Upload mined data back into CRM Once clusters have been determined, it is possible to use this data a number of ways: 1. Onsite optimization through A/B testing 2. Automatic content personalization display certain products based on previous purchase patterns 3. Prospecting through DoubleClick 4. Up and Cross sells 5. Understand specific user behaviors if a user purchases roughly the same day every month (pay day), distribute an incentivized and remarket automatically By understanding your user base in greater detail, you can significantly increase your CVR, ultimately increasing revenue. In addition, due to Google Analytics Premium s native integration with DoubleClick, it is possible to feed your converted user list into DCM/DBM and prospect accordingly, finding similar users (demographics, interests, etc) to reach via display.

7 User Flow Analysis (Registration & Purchase) Optimizing website/app to increase conversions Understanding how users navigate throughout your website is of vital importance for a number of reasons, for example: 1. You can directly influence the likelihood of a registration/ purchase by simply understanding common patterns 2. There may be technical errors that are preventing users for registering/purchasing. Understanding flows can prevent these issues cropping up 3. Simple tweaks can make huge differences. You d be amazed at how a simple tweak of a banner or a form field can directly influence users purchasing your goods Fortunately, Google Analytics Premium has a direct integration with BigQuery. For those who aren t familiar with BigQuery, it s a big data cloud-based analysis platform that enables querying massive datasets within seconds. BigQuery is SQL driven, but available for numerous client libraries such as Python, R, and so on. As Google Analytics Premium provides access to all of the unsampled data, it s possible to export this into BigQuery for analysis. This comes with numerous benefits itself: 1. BigQuery enables use of the timestamp. This makes page and path analysis significantly more granular and can be exported and coupled with additional dimensions and content groups 2. It s possible to merge CRM data with unsampled data from Google Analytics Premium. This is huge. We re able to identify the highest spending shoppers based on customer lifetime value and understand exactly how they found the site, what their common behaviors are, and how we can find more like these through prospecting in DoubleClick 3. We can directly upload our prospecting list into DoubleClick for mirroring patterns and acquiring similar high value customers 4. Since a cookie ID present, if that user registers from the same device & browser, it s possible to gauge pre-registration behaviors for optimization As you can imagine, there are endless numbers of user flows present in the unsampled data, but BigQuery can make this easier by mining the data, clustering and visualizing.

8 User Flow Analysis (Registration & Purchase) Understanding these flows, optimizing the site around common patterns and identifying any troublesome areas have proven to increase conversion rates for our clients. Google Analytics Premium has been instrumental in determining which areas to focus on, particularly where ecommerce is involved. As mentioned, it s possible to spend huge amounts of marketing bringing users to the site, but if the site is poorly optimized, you re limiting your chances of converting these users.

9 Targeted Display Marketing Leverage DBM/DCM for engagement-based audience lists Using a tactful approach to your display marketing can increase your chances of a successful campaign, whether for awareness or remarketing. When using DoubleClick as a standalone channel, you can add data into DoubleClick by using Floodlight tags (Counter, Sales and u= variables). These would be implemented on all of your pages, certain in-page elements and confirmation pages. This can be fairly time consuming to both implement and maintain. Fortunately, Google Analytics Premium has a native integration with DCM and DBM, enabling you to bypass the Floodlight tags and utilize the audience data for your remarketing lists. This makes it possible to feed engagement-based metrics such as time on site and pages per session, into your audience lists for remarketing. As an example of how this can impact your remarketing campaign, here are two scenarios: Floodlight User lands on site, adds product to basket, does not convert - remarket Google Analytics Premium User has been to the site twice, they ve spent 3 minutes or more per session, they ve added a product to basket, entered data into 2/3 of the payment form fields, haven t converted and haven t been back to the site in 2 days remarket with additional budget. As you can see with the above scenario, creating granular remarketing lists and applying budgets to user groups that have a significant likelihood to convert will have a greater ROI from your display campaigns.

10 Targeted Display Marketing In addition, it is possible to pull both View-Through and Click-Through data into your attribution models. This is a necessity for analyzing the performance of display in correlation to your other marketing channel activity. For example, based on this, you ll be in a position to understand what keywords facilitate your awareness-based display activity. We ve recently capitalized on the integration for Nestlé Dolce Gusto where we ve seen huge uplifts in conversions, enabling us to pinpoint exact segments of audiences on the brink of conversion while simultaneously reducing wastage on unengaged users. For anyone in the ecommerce sector, we highly advise looking into Google Analytics Premium to understand your audience and supplement your display activity.

11 If you want to get more out of your Google Analytics then contact us today