2. A/B build and reporting
3. Implementing onsite content / merchandising where we cannot access via our CMS
4. Onsite …
1) Test conversion rate optimisation changes to the user experience, primarily the purchase …
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Data is collected using Qubit’s own QProtocol data layer, or by integrating the user’s existing model via our API. Quantitative visitor behavioral data is combined with qualitative visitor feedback and ingested data from Qubit users' other systems of record enabling them to identify areas of the site and customer groups to optimize and target with personalization experiences.
Users can A/B test any changes to their site using Qubit, and the user interface lets them know what the test results are.
- Supported: Website Personalization Technology
- Supported: Visitor Analytics and Insights
- Supported: Business Intelligence
- Supported: A/B Testing Platform
- Supported: Tag Management
|Small Businesses (1-50 employees)||5%|
|Mid-Size Companies (51-500 employees)||45%|
|Enterprises (more than 500 employees)||50%|
|Supported Countries||UK, USA, France, Germany, Netherlands, Spain, Italy|
|Supported Languages||Our service can process all major languages|
Frequently Asked Questions
- We are able to query various details about the customer that would otherwise be extremely difficult, in order to identify geography or device types to affect their experience. We've consistently seen good return on often minor updates to the UI.
- As Qubit collects vast amounts of detail from our site we're able to test advanced functionality to validate theories that might otherwise be difficult to quantify. Their attribution algorithms seem to do a good job of projecting the effect of tests
- Qualitative tests, such as feedback request forms have helped add to our interaction with customers, and have helped identify key areas on the site and in our offerings that we are able to address.
- Unfortunately, we weren't able to leverage Qubit's end-to-end data and analytics capabilities. We had an established analytics tool which they weren't able to integrate with, so we had to map data as a work around.
- We found Qubit's dashboards and data collection methods useful in quickly understanding how tests were performing and deciding on next steps.
- Although there were limitations in mapping data or needing to scrape our site rather than read directly from Qubit's data layer, Qubit still helped us find ways to effectively execute most of the initiatives we identified.
- The Qubit platform and service has reduced our reliance on our internal IT team to implement changes on site.
- Test hypothesis can be created relatively quickly and the test outcome, either conclusive or inconclusive, provides answers that would not otherwise be very difficult to answer.
- The platform and process helps to introduce a culture of using evidence to make decisons.
- This is honestly an area that we haven't been able to make work for us.
- The reports generated from the tests completed on the website have been the deciding factor in a large amount of decisions within the company.
- The fact that Qubit isn’t merely the middleman to deliver tests and provide tags is one of their best features, they are included in the whole process from the design and implementation all the way through to the analysis of the results and provide suggestions on the ways forward.
- We can easily measure what impact the changes we made have on the conversion rate.
- We feel liberated, being able to do anything we feel is right. And we can test the theory first - taking opinion/emotion out of the equation. Let the numbers speak for themselves.
- We are able to test and refine development ideas first - before having to raise any internal Dev tickets. Amazing!
- Targeted website personalisation such as first time visitor prompts, market segmented content, feedback collection and many more.
- Product recommendations, starting from the data they collect on what our customers do and buy, to calculating products to recommend and then delivering the content.
- Email targeting - We are running email campaigns using data gathered by Qubit to drive when emails are sent and the content in them, and the delivery of those emails.
- Data collection - visibility and segmenting
- The above point helping us preparing the right experience and targeting the right segment
- Set goals to these experiences and understand our customers better
- Able to make more informed decisions based on the holistic view of data
- Able to have different customer experiences based on how different segments reacted to product recommendations and tests
- This has been our largest challenge based on our current IT infrastructure. We are working toward a more robust Data Integration with Google Big Query, but our own internal resource constraints have slowed the process.
- The segmentation data included in our A/B Testing has been key to better refining our personalization for our customer base both by acquisition and channel specifics.
- Having everything in one platform is always a winner for ease, practicality and measuring.
- Having all these features in a single platform saves money, time and resources.
- It allows us to learn from that huge amount of data and use it with barely any effort.
- Though Qubit is capable of collecting a lot of data, there is no productised way to access this data.
- This is the first time we have had an end to end view of website visitors, at customer level. Further, we are able to look at how changes we've made via Qubit have impacted user behaviour. It has allowed us as a business to be more data-led when we think about making changes to our site, and has encouraged a 'test and learn' mentality. Changes which we would previously have simply made to the site are now put through Qubit, so we can test impact before we go fully live.
- This end-to-end data has not yet been fully utilised due to other dependencies within the business, but the fact that we have it means that we've already got a whole load of historic data that we can link to individuals when it comes to looking at how we can truly personalise the website experience.
- Before a change on the website we make some test and we learn.
- We correlated customer opinion with contextual information.
- We are looking to the data.
- An A/B test is not just having a whim of an idea and using a tool to implement it to see what happens. We have a strategic team here that uses various data points, including those offered by Qubit, to conceive of tests that could have a high impact on various KPIs and "move the needle" so to speak.
- The preview tool/feature in Qubit is easy to use and reliably indicative of the actual user experience post test launch. It also makes it easier to send clients links for their own testing/QA before we launch a test.
- The reporting/metrics in the dashboard occur in real time and are a great way to see how any given test/experience is performing as well as gain valuable insight for future iterations/ideas. The Qubit team is also very responsive and will accommodate custom data/reporting requests promptly.
- It allows us to see what specifically customers are engaging with and make quick changes based on that data.
- Allows for better coordination between technical and non technical teams.
- Allows us to respond quickly to problems that need fixing.
- We now are clearly able to see the whole picture of our user experience to allow us to present back to them the ideal shopping experience.
- Transformed the way we price
- Transformed the home page
- Step changed upsell
- The QuBit data layer is extremely useful in tapping into customer segments which we couldn't previously (and of course testing whether there is value in marketing specifically to those new segments as a new group).
- The data collection elements of the platform are very useful, although it was tricky to use this data across multiple platforms (email, etc).
- It hasn't as of this date (Jun-16). But that's because we haven't made full use of the Qubit technology due to internal reasons. We intend to use Qubit to it's fullest in Q2 of the next financial year.
- Better decision making
- Better ROI on marketing investments
- Better customer experience
- Clarity in decision making - analytical validation is critical to our ability to assess whether any given assumption about the impact of a change to the site on customer behavior is borne out in actuality.
- In-house creative control - the high degree of customizability that Qubit affords gives us complete in-house control over the variations that we deliver. It's definitely a plus that when you want to make some minor adjustments to a variation, you generally don't have to reach out to an external agent.
- Custom event tracking - we use the custom event tracking feature in many of our Qubit layers to assess the impact of variations on goals that are important to us specifically, but may not be applicable to other companies.
- Save Time: do not integrate several solutions together.
- No headaches: same KPI along all actions - analytics, personalization, A/B testing.