On-Demand Webinar: Reviewing Ecommerce Fundamentals
Outlined below are some of the overarching lessons to help you understand your customer’s needs. It’s important to remember, it’s not the individual site elements but the overall customer response to the combined elements that matters. You may believe you have the best site possible but it is important to be continually listening to the customer to understand their responses. To be successful in ecommerce you must also place emphasis in two foundational planning areas.
I have observed the single biggest ingredient of a high performing ecommerce digital analytics team is how well they work together with stakeholders. A digital analytics team cannot go it alone and produce great results. There need to be shared learnings, cooperation and accomplishments to hold together an organization. Make sure the lines of communication between analytics and the rest of the business are open and strong in all directions. Check in with your stakeholders on at least a monthly basis and have the right analytics request processes in place.
Always be mindful of the driving business unit forces at your company. I have observed strong merchandiser focused organizations and others more marketing forward. It is important to respect that heritage to earn trust and then align your digital analytics efforts in these areas.
Data Quality and Governance
An implementation’s longevity is often only as good as its documentation. Invest the time here and your group will save a lot of pain down the road. Without a doubt with the recent expansion of custom events and custom conversion variables this area is more important than ever. If you get behind with documentation the situation can get out of control and make any transitions rocky.
Digital analytics outreach should touch all areas of the company. Come to agreement on reporting strategy within ecommerce across teams. Be a central hub for information and you will find you get invited to projects earlier and ingrained into the results evaluation. Make sure you always have an eye on your data coming through. Set up automated checks and reports to monitor your data to keep quality high.
Also remember the real value in ecommerce analytics is within those pre-purchase and browse behavior indicators; not the end static sales data. Take advantage of integrations with other systems and spread your digital analytics reach into other areas of the business.
With a strong foundation built with stakeholder alignment and governance, then you can start to look towards specific implementation techniques and analysis methods that are vital to an advanced ecommerce implementation.
Add Potential Revenue upon Cart Add– Allows you to see at a product level where money is being left on the table and which customer segments by value levels have the propensity to abandon.
Promotions & Discounts Tracking- Track application and conversions with promotions and discounts to assess impact on cart activity and conversions.
Primary SKU & Secondary SKUs– Make sure to apply tracking at each level from Parent down to Child SKUs. Once a customer makes a choice such as Size, Color, and Customizations your tracking should always reflect that level of detail even if it requires tracking SKU levels across several different data dimensions.
Merchandising Hierarchy Location- Tracking your merchandise hierarchy against your products allows you to see the impact of your site product positioning efforts. This tracking allows you to track performance if the same product is merchandise in multiple areas of the site.
Product Finding Methods- How the customer finds product produces vital insight on an ecommerce site. You can then optimize the experience to encourage interaction with the best performing features.
Dark Social Tracking- Dark Social represents that portion of traffic or conversion that should be attributed to social sites like Facebook and Twitter. Ben Gaines outlines how to track dark social traffic via processing rules in his article Shedding Light on Dark Social with Adobe Analytics
Entries & Exists Metric– You can apply this metric across other report dimensions to see the first value captured and the last value captures at a visit level. You can take this even further by using sequential segmentation and creating slices of data that cross visits.
Classify Products by Season/Month/Year Introduced- Track the conversion performance of your product mix across introductory phases and understand product lifecycles through classification metadata that goes beyond.
Create Metrics Using Segments- Segmented metrics are a game-changing feature that released in June this year within Reports & Analytics. The metrics that you can bring into reports are derived at report run time and potentially you are no longer bound by technical implementation updates.
IF Conditional Statements- One of the top uses cases for calculated metrics. Your reports can now accurately reflect your desired traffic levels and bounds by setting a value floor and/or ceiling for any given metric. The calculated metric logic is helpful for sorting reports that rely on rate % ranked sort like bounce rate or conversion rate against traffic levels that matter.
IF Percentile of Demand (Revenue & Units)- IF statements work well at a base individual product level and allow you to identify statistical band ranges of your product top sellers and basement dwellers.
Z-Score Advanced Function- Z-Score is an advanced calculated metric function that indexes your data within a normal distribution. The number represents the count of standard deviations an observation is from the mean (0 score). A powerful measure to see how far apart your dimensions are performing against each other.
Site Interactions Scoring of Traffic Groups- You can combine site interactions into a single ‘score’ formula to derive a blended % of visits rate. Use this calculated metric scoring as a trend metric for marketing channels & traffic sources to evaluate performance over time.
Time Prior to Event- Evaluate the amount of time that passes before key conversion events on site. This stock report is available under the Site Metrics menu in Reports & Analytics.
Customer Attributes- For authenticated and identified visitors find out which content is consumed by different customer-levels and how conversion performance varies. The customer attributes are based on your customer record uploads to the Marketing Cloud. You can analyze product affinities across loyalty status, gender, brand affinity, etc.
- First and most importantly, invest time up front and plan well. In order for your digital analytics program to be successful it has to have buy in and collaboration with all the key stakeholders in the business. Work towards earning the trust of others through a well-thought out tracking design & standards. I have not seen an analytics group function to the best of their capabilities without all the foundational planning pieces in place.
- Second take a hard look at the process before your conversion end points. High opportunity areas in digital analytics are often in those early stages of the consideration process. Make sure you have a strong base implementation, but always look to be creative and extend your tracking insights. There is a wealth of information with an ecommerce site and the hard part can be distilling down what truly matters to the customer.
- And last leverage the new enhancements in Adobe Analytics to reduce data outlier noise and cut down to key indicators. Be sure to consistently have a drive to analyze trends at a customer level. Look to match affinities and trends across customer groups to inform your marketing and merchandising efforts. Focus on the fundamentals around selling more merchandise, to more customers, more often, at higher average order value levels. Conversions happen in a context. Analytics should help bring clarity to all the complications of an ecommerce site.
Check out a recording of the webinar.