Why are metrics in google analytics different?
The figures presented in the exposure strategy view are the based on what is notified to Voyado Elevate. If these figures differ from what Google Analytics show, it is likely due to discrepancies in how information is provided to the different tools.
Ensure that all orders are properly notified to Voyado Elevate and that both cost and selling price are specified accurately in each order notification.
What is an exposure strategy?
The end goal for Voyado Elevate is to maximize the sales on your website. That is what drives the internal algorithms in deciding what content to expose. But, the concept of maximizing sales is ambiguous and could refer to several things, e.g. increasing the number of sold units, the number of converted sessions or the generated revenue.
Different strategies might influence your site to affect these goal metrics in different ways, and it is not always certain that they will be aligned. Therefore, Voyado Elevate presents the possibility of choosing strategy for your site, in order to aim for different goals.
Key use cases:
- Test how different exposure strategies performs on your site then make an informed choice on what exposure strategy delivers the best result for you in each market.
- Track top level performance metrics over time and correlate your marketing activities to performance.
What strategy should I choose?
Expose products that sell more: This will favour products that have performed well with regard to sold units. This strategy should be used when converting customers is more important than e.g. revenue or profit. This is recommended for e.g. new markets or sale periods where acquiring new customers is the primary focus.
Expose higher priced products: This will favour products that have generated higher revenues historically. This will, on most sites, be the best choice if maximizing your revenue is your primary focus. You will likely see higher priced products higher up in your listings when selecting this strategy.
Expose high margin products: This will favour products that have generated better profit historically. This will, on most sites, be the best choice if maximizing your profit is your primary focus. You will likely see more profitable products higher up in your listings when selecting this strategy.
Note: There are trade-offs for each strategy, meaning that when selecting e.g. "Expose high margin products" as your exposure strategy, you might increase your profit but at the cost of a revenue and conversion loss. Similarly, when selecting "Expose products that sell more", you might gain conversions but at the cost of potential profit and revenue. In order to make an informed decision about the level of gain or loss you can expect with regards to the different metrics, when switching strategy, it is highly recommended that you run an A/B test first.
Which functions support exposure strategies?
Exposure strategies are fully utilized in:
- Product lists, normally used on category pages, when using relevance or sales as sort order
- Search hits, when using relevance or sales as sort order
Exposure strategies are partially utilized in:
- Product lists, normally used on category pages, when using personal as sort order
- Autocomplete
- Did-you-mean
- Product suggestions
Functions that partially utilize exposure strategies use exposure strategies on product backfill.
What are strategy areas?
Strategy areas refers to all areas which potentially can influence your customers by altering their product ranking, based on the current exposure strategy.
For an area to be able to influence a customer, it must use a function which supports exposure strategies. This includes search, product lists - normally used on category pages, and products presented in ads.
What are affected sessions?
Affected sessions refer to the proportion of sessions that potentially have been influenced by the choice of exposure strategy. Customers can be influenced when interacting with a strategy area, i.e. when searching or navigating using category pages.
An example of a session not affected by the current strategy, is when a customer purchases something directly through a product page, without navigating there via Voyado Elevate.
How do I increase affected sessions?
Ensure that all functions which are supported are implemented properly and that they default to supported sort orders. E.g. if you support multiple sorting options on category pages, ensure that relevance is the default sort order. When this is done, affected sessions will vary depending on the behavior of your customers.
What is an A/B test?
When choosing a certain strategy, Voyado Elevate makes different trade-offs to aim for different goals. E.g. when exposing products that have generated a lot of revenue in the past, the overall number of conversions might go down as more expensive products will generally be exposed. This trade-off depends on various factors such as the price range of your assortment and the type of customers that your site is attracting. If your customers are open to inspiration, switching between different strategies will likely have a bigger impact than if a majority of your customers know precisely what to buy.
An A/B test will establish the effect of switching exposure strategy on your site, by splitting the traffic on your site into two groups, each facing one of the two strategies being evaluated. The results of this test provide you with more information about what effects the different strategies have on your goal metrics, and inform you of potential trade-offs.
Why should I run an A/B test?
When switching exposure strategy trade-offs are made. We recommend that you estimate the impact on your site before changing. The result of an A/B test will show indications of how your conversions and revenue will be affected, if you decide to change strategy.
When should I stop the A/B test?
For each metric, the potential effect of switching to the evaluated strategy is given as a span. It is calculated that 95% of the time, the actual outcome of the switch will be somewhere in this span. This means that you can be reasonably certain what effect the switch will have for a certain metric, if the span is relatively small.
Initially the span will be very large, making it hard to draw sound conclusions, but the predicted impact generally becomes more precise over time. How fast the predictions converge mainly depends on the amount of traffic on your site, and how much of it is affected by the exposure strategy.
It is however possible that the span increases due to inconsistencies or sudden changes in behavioral patterns. This indicates that the outcome has become less certain and is now more difficult to predict.
You should stop the A/B test (or switch to the new strategy) when the predicted spans of the metrics you are interested in are sufficiently small, such that you are able to make an informed decision. In rare cases, conclusions can be drawn even if the span sizes are large. For instance, if the lower bound is above zero, the switch will very likely be positive for that metric. Similarly, if the upper bound is below zero, the switch will very likely be negative.
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