In this paper we examine the quality of data on household expenditure obtained using a receipt scanning App in a nationally representative household panel study. We invited 2,432 members of the UK Household Longitudinal Study Innovation Panel to download an App to report all their spending on goods and services for a month. Respondents were asked to each day scan all receipts, report spending for which they did not have receipts, or report that they had not made any purchases that day. The incentive scheme included an experiment with a conditional incentive of £2 versus £6 for downloading the App, followed by a daily conditional incentive of £0.50 for using the App, and a £10 bonus for using the App every day. The App data collection is will be completed early December 2016. We will examine and report on various aspects of data quality. Firstly we will examine participation rates at various stages of the data collection: What proportion of the sample had the required technology (a smartphone or tablet) to participate in the task? What proportion had said they were hypothetically willing to participate in such a task? What proportion actually downloaded the App? How did participation evolve over the month? What impact did the conditional incentive for downloading the App have? Secondly we will examine biases in the types of sample members who participated, considering social-demographic characteristics, financial position and behaviours, mobile device ownership, usage patterns and self-rated skills, and indicators of cooperativeness collected in previous waves of the panel. Third we will examine estimates of monthly individual and household expenditure, comparing the App data with expenditure data from previous waves of the panel, as well as drawing on respondent self-assessments of the proportion of expenditure missed due to non-participant household members, drop-out and under-reporting.