In this episode we sit down with Bill Barton, chief product & engineering officer at Rokt, to discuss how the technology is being used by retailers to generate measurable revenue uplifts.
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- What problems Rokt is helping ecommerce businesses solve
- How the technology is being used by retailers
- Key product features & business tooling
Having recently talked about profit optimisation for ecommerce with Hypersonix, we’re drilling down into technology solutions that help ecommerce teams improve monetisation of the onsite conversion funnel and today our focus is on Rokt.
Rokt helps retailers to generate incremental revenue through targeted on-site advertising. Unlike typical ad placements, Rokt sits post-transaction, so the customer experience is maintained and the impact on revenue and repeat purchasing can be accurately measured. Listen to chief product & engineering officer Bill Barton discuss how the product works.
- What are the key ecommerce challenges that Rokt is trying to address with its technology?
- You focus on the cart to confirmation page purchase funnel, so please walk us through the most common user journey where Rokt is working on an ecommerce store, and what role you’re playing at each step.
- Can you give us a few case studies for where your tech has been used successfully by a retailer – how have they used it, what results did they see?
- You talk about turning the payments page into a profit center – typically nobody touches the payment page for fear of screwing conversion, can you talk us through the offering here?
- Coming back to hold out tests to compare a cell that doesn’t see any Rokt campaigns during the cart to checkout flow vs. a cell that does, how can this be done? HOW DO YOU TARGET SPECIFIC USER TYPES or exclude specific users?
- How does this work in a multi-storefront setup: how can the campaigns be targeted at a country or language level?
- How does a new merchant set up Rokt to connect it to all the different potential offers and promotions: what effort is involved, how much is automated by connecting it to other 3rd party systems vs. manual configuration?
- Your product is designed to assess a customer’s likelihood to engage – how is this calculated, what data are you using and what signals influence the likelihood rating?
- How important is historical data to warm the algorithms & how can new sites benefit from the tech from a cold start?
- In addition to the hold-out tests, what other A/B testing options are there to compare different strategies and optimise KPIs like conversion and revenue?
- How are the partner ad offers managed – is this your own ad network a merchant connects to, or do they need to have the commercial agreements in place themselves?
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