Retail sales, Great Britain: April 2016

A first estimate of retail sales in volume and value terms, seasonally and non-seasonally adjusted.

This is not the latest release. View latest release

This is an accredited National Statistic. Click for information about types of official statistics.

Email Melanie Richard

Release date:
19 May 2016

Next release:
16 June 2016

1. Main points

The volume of retail sales in April 2016 is estimated to have increased by 4.3% compared with April 2015.

The underlying pattern in the data, as suggested by the 3 month on 3 month movement in the quantity bought, increased by 0.3%.

Compared with March 2016, the quantity bought in the retail industry is estimated to have increased by 1.3%.

Average store prices (including petrol stations) fell by 2.8% in April 2016 compared with April 2015.

The amount spent in the retail industry increased by 1.2% compared with April 2015 and increased by 1.0% compared with March 2016.

The value of online sales increased by 9.3% in April 2016 compared with April 2015 and increased by 1.7% compared with March 2016.

Revisions to this release were caused by the incorporation of late data. The earliest revisions point for current price, non-seasonally adjusted data was March 2014. More information on revisions can be found in the background notes.

Back to table of contents

2. About this release

This bulletin presents estimates of the quantity bought (volume) and amount spent (value) in the retail industry for the period 3 April 2016 to 30 April 2016. Unless otherwise stated, the estimates in this release are seasonally adjusted. Estimates for April 2016 do not include Easter, whereas Easter 2015 fell in the April 2015 reporting period.

The estimates in this release are based on a monthly survey of 5,000 retailers, including all large retailers employing 100 people or more and those with annual turnover of greater than £60 million who employ 10 to 99 people. It is estimated that this survey covers approximately 95% of all known retail turnover in Great Britain.

The quality of the estimate of retail sales

Retail sales estimates are produced from the Monthly Business Survey – Retail Sales Inquiry (RSI). The timeliness of these retail sales estimates, which are published just 3 weeks after the end of each month, makes them an important early economic indicator. The industry as a whole is used as an indicator of how the wider economy is performing and the strength of consumer spending. Results are revised for the previous 13 published periods. More information about the data content for this release can be found in the background notes.

Revisions are an inevitable consequence of the trade-off between timeliness and accuracy. The response rate in April 2016 was 61.6% of questionnaires, accounting for 93.7% of registered turnover in the retail industry. Therefore, the estimate is subject to revisions as more data become available.

All estimates, by definition, are subject to statistical uncertainty and for the retail sales index we publish the standard error associated with the non-seasonally adjusted estimates of year-on-year and month-on-month growth in the quantity bought as a measure of accuracy. More information on these standard errors can be found in the background notes and in the quality tables of this release.

We are continually working on methodological changes to improve the accuracy of the retail sales estimates; progress on these can be found on the continuous improvement page.

The datasets offer different ways to access the data, they include:

  • non-seasonally adjusted and seasonally adjusted volume and value indexes by industry
  • year-on-year and month-on-month growth rates by industry
Back to table of contents

3. Main figures

At a glance

In April 2016:

the quantity bought in the retail industry (volume):

  • increased by 4.3% compared with April 2015; this was the 36th consecutive period of year-on-year growth
  • increased by 1.3% compared with March 2016

the amount spent (value):

  • increased by 1.2% compared with April 2015
  • increased by 1.0% compared with March 2016

Amount spent in the retail industry

In the 4 week reporting period during April 2016, the amount spent in the retail industry was £28.1 billion (non-seasonally adjusted).

This compares with:

  • £34.4 billion in the 5 week reporting period for March 2016
  • £27.6 billion in the 4 week reporting period for April 2015

This equates to an average weekly spend of:

  • £7.0 billion in April 2016
  • £6.8 billion in March 2016 and
  • £6.9 billion in April 2015
Back to table of contents

4. Sector summary

Main points

In April 2016:

  • all store types, except textile, clothing and footwear stores showed increases in the quantity bought compared with April 2015
  • there were decreases in textile, clothing and footwear stores, household goods stores and fuel stores in the amount spent compared with April 2015
  • all store types saw falls in average store price compared with April 2015
  • non-seasonally adjusted data show that the prices of goods sold in the retail industry (as measured by the implied price deflator) decreased by 2.8%; this was the 22nd consecutive month of year-on-year price falls

More information on how the implied price deflator and other estimates in this release are calculated, can be found in section 3 of the background notes.

Back to table of contents

5. Focus on textile, clothing and footwear

Textile, clothing and footwear stores consist of 3 different store types. Table 3 shows the store types, respective weights in retail sales, year-on-year seasonally adjusted growth rates and average store price.

We can see that clothing stores contribute the most to this sector while textiles and footwear are much smaller.

In April 2016, there were falls of 6.3% in the quantity bought and 6.0% in the amount spent in textile, clothing and footwear stores compared with April 2015. There were falls in the quantity bought and amount spent in textile and clothing stores while footwear was the only store type to show an increase in both measures year-on-year. Feedback from retailers suggests that the poor performance year-on-year could be due to the early Easter and unseasonal weather affecting summer clothing ranges.

Figure 1 shows the quantity bought, amount spent and average store price in clothing stores over a longer time period.

Looking at the short-term picture, April 2016 compared with March 2016:

  • quantity bought increased by 1.7%
  • amount spent increased by 2.1%
  • average store price fell by 0.4%

After the weakness in the year-on-year picture in clothing stores, the increases month-on-month in the quantity bought and amount spent could be seen as unusual, however, the chart shows that the monthly series is volatile and seems to be affected by changes in price. In the latest period average price in store fell and both the quantity bought and amount spent increased, whereas, we saw the opposite effect in March 2016, where prices increased and the quantity bought and amount spent fell.

Back to table of contents

6. Internet sales in detail

Seasonally adjusted internet sales data are published in the RSI Internet tables and include:

  • a seasonally adjusted value index
  • year-on-year and month-on-month growth rates

Internet sales are estimates of how much was spent online through retailers across all store types in Great Britain. The reference year is 2012=100.

Main points:

  • average weekly spending online in April 2016 was £886.6 million; this was an increase of 9.3% compared with April 2015
  • the amount spent online accounted for 13.4% of all retail spending, excluding automotive fuel, compared with 12.4% in April 2015

Table 4 shows the year-on-year growth rates for total internet sales by sector and the proportion of sales made online in each retail sector.

Back to table of contents

7. Contributions to growth

The retail industry is divided into 4 retail sectors:

  • predominantly food stores (for example, supermarkets, specialist food stores and sales of alcoholic drinks and tobacco)
  • predominantly non-food stores (for example, non-specialised stores, such as department stores, textiles, clothing and footwear, household goods and other stores)
  • non-store retailing (for example, mail order, catalogues and market stalls)
  • stores selling automotive fuel (petrol stations)

Figure 2 shows that for every pound spent in the retail industry:

  • 40 pence was spent in food stores
  • 43 pence in non-food stores
  • 8 pence in non-store retailing
  • 9 pence in stores selling automotive fuel

Using these as weights, along with the year-on-year growth rates, we can calculate how each sector contributed to the total year-on-year growth in the quantity bought.

In April 2016 compared with April 2015, all 4 main retail sectors saw an increase in the quantity bought (volume) while all main sectors, except petrol stations saw an increase in the amount spent (value). The largest contribution in the quantity bought came from food stores while the largest contribution in amount spent came from non-store retailing.

In April 2016 compared with March 2016, 2 of the 4 main retail sectors (non-food stores and non-store retailing) saw an increase in the quantity bought (volume) while 2 of the 4 main sectors (non-food stores and petrol stations) saw an increase in the amount spent. The largest contribution for both quantity bought and amount spent came from non-food stores.

Back to table of contents

8. Distribution analysis

Table 5 shows how sales varied among different-sized retailers. It shows the distribution of reported change in sales values of businesses (from the RSI sample), ranked by size of business (based on number of employees).

Businesses with 40 to 99 employees saw the largest growth in the amount spent in April 2016 compared with April 2015 (28.8%). Businesses with 100 and over employees showed an increase of 2.0%.

More information on the performance of the retail industry by store type and size can be found in the Business Analysis dataset.

Back to table of contents

9. Economic context

Figure 5 compares a rolling 3 month period with the same period in the previous year and highlights that the volume of retail sales started to grow strongly from mid-2013. The latest data show a slight decrease in the retail sales growth from 3.9% in the 3 months to March 2016 to 3.7% in the 3 months to April 2016. The rolling 3 month on 3 month a year ago growth in retail sales has averaged 3.8% since the start of 2016 which was lower than the 2015 average of 4.6%.

Three distinct periods emerge from Figure 5. Between April 2007 and July 2008, retail sales volumes were experiencing continuous growth, although to a different degree. Growth in inflation (Consumer Prices Index CPI) was lower than average weekly earnings over most of this period; which resulted in rising real earnings, an indicator of the purchasing power of consumers. Moreover, between April 2007 and July 2008, consumer credit increased by 8.8%, which may have been a factor driving retail sales growth.

However, between August 2008 and May 2013, the volume of retail sales fluctuated between periods of contraction and expansion, which may be partly explained by the economic climate over this period, and coincided with a reduction in consumer credit of 24.8%. Moreover, growth in average weekly earnings was lower than inflation over most of the period, which implies that earnings fell in real terms.

The third period shown in Figure 5 started in June 2013, when growth in volume terms began to increase notably, despite average weekly earnings growing at a slower rate than CPI until September 2014. Moreover, since June 2013, consumer credit has followed a broadly upward trend, growing by 16.6% between June 2013 and March 2016. Between June 2013 and April 2016, the price level (shown by the implied deflator) fell by 5.8%, coinciding with 11.9% growth in the volume of retail sales over this period. In addition, this upturn in spending has been accompanied by a decline in the savings ratio, from an average of 9.0% over the period 2008 to 2012, to an average of 5.3% over the period 2013 to 2015.

Figure 6 breaks down the growth in total retail sales into the contributions made by predominantly food and non-food stores (which includes department stores, other stores, clothing, and household goods), non-store retailing, and petrol, between April 2007 and April 2016. In the 9 year period, non-store retailing has, on average, made the largest contribution to growth and is the only component to have made a consistently positive contribution. In the most recent period, all 4 components have made positive contributions to growth, with predominantly food and non-food stores contributing the most, 1.5 percentage points and 1.0 percentage points, respectively. In the latest month, growth continues to be driven by a broad based increase in all 4 categories.

Back to table of contents

10. International data

The only international estimate of retail sales available for April 2016 was published by the US Census Bureau on 13 May 2016. In its advanced retail sales estimates for April 2016, the amount spent in the US retail industry, including motor vehicles and parts and food services, increased by 1.3% compared with the previous month and increased by 3.0% compared with April 2015. Total sales for the 3 months to April 2016 were up 2.8% from the same period a year ago.

The latest estimates of the volume of retail trade across the European Union, from Eurostat for March 2016, show the seasonally adjusted volume of retail trade decreased by 0.5% in the euro area (EA19) and fell by 0.7% in the EU28 when compared with February 2016. Compared with March 2015, the retail sales index increased by 2.1% in the EA19 and by 2.4% in the EU28. Note that an accurate comparison cannot be made as Eurostat data are calculated on a 2010 = 100 basis, while data for Great Britain are calculated on a 2012 = 100 basis.

Back to table of contents

.Background notes

  1. What’s new

    We have introduced electronic data collection for respondents on the Monthly Commodity Inquiry for the first time in April 2016.

    Due to essential maintenance the retail sales data will not be available on the explorable datasets page until Monday 23 May 2016.

  2. Understanding the data

    i. Quick Guide to the Retail Sales Index

    ii. Interpreting the data

    The Retail Sales Index (RSI) is derived from a monthly survey of 5,000 businesses in Great Britain. The sample represents the whole retail sector and includes the 900 largest retailers and a representative panel of smaller businesses. Collectively all of these businesses cover approximately 90% of the retail industry in terms of turnover.

    The RSI covers sales only from businesses classified as retailers according to the Standard Industrial Classification 2007 (SIC 2007), consistent with the international NACE Rev 2 classification of industries. The retail industry is division 47 of the SIC 2007 and retailing is defined as the sale of goods to the general public for household consumption. Consequently, the RSI includes all internet businesses whose primary function is retailing and also covers internet sales by other British retailers, such as online sales by supermarkets, department stores and catalogue companies. The RSI does not cover household spending on services bought from the retail industry as it is designed to only cover goods. Respondents are asked to separate out the non-goods elements of their sales, for example, income from cafes. Consequently, online sales of services by retailers, such as car insurance, are also excluded.

    The monthly survey collects 2 figures from each sampled business: the total turnover for retail sales for the standard trading period, and a separate figure for internet sales. The total turnover will include internet sales. The separation of the internet sales figure allows an estimate relating to internet sales to be calculated.

    iii. Definitions and explanations

    The “value” or current price series records the growth of the value of sales “through the till” before any adjustment for the effects of price changes.

    The “volume” or constant price series are created by removing the effect of price changes from the value series. The Consumer Prices Index (CPI) is the main source of the information required on price changes. In brief, a deflator for each type of store (5-digit SIC) is derived by weighting together the CPI components for the appropriate commodities, the weights being based on the pattern of sales in the base year. These deflators are then applied to the value data to produce volume series.

    The “implied deflator” or “the estimated price of goods” is derived by dividing the non-seasonally adjusted value and volume data to leave a price relative. In general, this implied price deflator should be quite close to the retail component of the CPI. More information on the implied price deflator can be found in the Quick Guide to Retail Sales.

    iv. Use of the data

    The value and volume measures of retail sales estimates are widely used in private and public sector organisations, both domestically and internationally. For example, private sector institutions such as investment banks, the retail industry itself and retail groups use the data to inform decisions on the current economic performance of the retail industry. These organisations are most interested in a long-term view of the retail sector, taken from the year-on-year growth rates. Public sector institutions use the data to help inform decision and policy making. They tend to be most interested in a snapshot view of the retail industry, which is taken from the month-on-month growth rates.

    In a recent survey users found the Retail Sales Index statistics important to their work. It was found crucial for financial modelling of sectors and recognised as a timely indicator for the economy. It has been used as a comparative tool with BRC and other market sources to boost context. Practically, it has been utilised as a comparative tool for business performance and the ability to access internet retail sales has been particularly beneficial to some. On a non-industry level, the RSI was perceived as important for informing political opinions or simply for curiosity by individuals who were not necessarily utilising it as a reference for work purposes.

    The Retail Sales Index feeds into estimates of GDP in 2 ways. Firstly, it feeds into the services industries when GDP is measured from the output approach. Secondly, it is a data source used to measure household final consumption expenditure, which feeds into GDP estimates when measured from the expenditure approach.

    The data feed into the first (or preliminary) estimate of GDP, the second estimate of GDP and the third estimate, published in the Quarterly national accounts.

  3. Methods

    Information on retail sales methodology is available on our website.

    i. Composition of the data

    Retail sales estimates are based on financial data collected through the monthly Retail Sales Inquiry. Response rates at the time of publication are included for the current month, and the 3 months prior. The response rates for those historical periods are updated to reflect the current level of response, incorporating data from late returns. There are 2 response rates included with 1 percentage for the amount of turnover returned, and the other percentage for the amount of questionnaire forms. Historical response rates are available in the quality information dataset.

    ii. Seasonal adjustment

    Seasonally adjusted estimates are derived by estimating and removing calendar effects (for example, Easter moving between March and May) and seasonal effects (for example, increased spending in January as a result of Christmas) from the non-seasonally adjusted (NSA) estimates. Seasonal adjustment is performed each month and reviewed each year, using the standard, widely used software, X-13-ARIMA-SEATS. Before adjusting for seasonality, prior adjustments are made for calendar effects (where statistically significant), such as returns that do not comply with the standard trading period (there is more information in the Methods, Calendar effects section), bank holidays, Easter and the day of the week on which Christmas occurs.

    The data collected from the retail sales survey estimate the amount of money taken through the tills of retailers; these are non-seasonally adjusted data. These data consist of 3 components:

    • “trend” which describes long-term or underlying movements within the data
    • “seasonal” which describes regular variation around the trend, that is, peaks and troughs within the time series (the most obvious is the peak in January and the fall in February)
    • “irregular” or “noise”, for example, deeper falls within the non-seasonally adjusted series due to bad weather impacting on retail sales

    To ease interpretation of the underlying movements in the data, the seasonal adjustment process estimates and removes the seasonal component. It leaves a seasonally adjusted time series made up of the trend and irregular components.

    In the non-seasonally adjusted RSI we see large rises in January each year and a fall in the following February, but these are not evident in the seasonally adjusted index. This peak in January is larger than the subsequent fall, but the trend and irregular components in both months are likely to be similar. This means that the movements in the unadjusted series are almost completely a result of the seasonal pattern.

  4. Quality

    i. Basic quality information

    The standard reporting periods can change over time due to the movement of the calendar. Every 5 or 6 years the standard reporting periods are brought back into line by adding an extra week. For example, January is typically a 4 week standard period but January 1986, 1991, 1996, 2002, 2008 and 2014 were all 5 week standard periods. The non-seasonally adjusted estimates will still contain calendar effects. If the non-seasonally adjusted estimates are used for analysis, this can lead to a distortion depending on the timing of the standard reporting period in relation to the calendar, previous reporting periods and how trading activity changes over time.

    The non-seasonally adjusted series contain elements relating to the impact of the standard reporting period, moving seasonality and trading day activity. When making comparisons, you should focus on the seasonally adjusted estimates as these have the systematic calendar-related component removed. Due to the volatility of the monthly data, growth rates should be calculated using an average of the latest 3 months of the seasonally adjusted estimates.

    When interpreting the data, the relative weighted contributions of the sectors in the all retailing series should be considered. Based on SIC 2007 data, total retail sales consists of: predominantly food stores 40.4%, predominantly non-food stores 42.6%, non-store retailing 7.6% and automotive fuel 9.4%.

    ii. Standard error

    Standard errors determine the spread of possible movements and are a means of assessing the accuracy of the non-seasonally adjusted month-on-month and year-on-year estimates of all retail sales volumes. The lower the standard error, the more confident we can be that the estimate is close to the true value for the retail population.

    The standard error of year-on-year movement for “All Retailing” is 0.9%. This has remained relatively stable, only varying marginally between 0.8% and 0.9% since 2012. The highest value was between August and September 2013 where the year-on-year movement increased to 1.0%.

    Table 7 shows the year-on-year movement for the non-seasonally adjusted chained volume measure alongside the standard error, across the published sector breakdowns for April 2015 and April 2016. The differences between April 2015 and April 2016 highlight that the standard error has decreased the most in “Automotive fuel”. The greatest increase was in “Household goods stores”.

    More information on standard errors can be found in the Retail Sales Quality Tables datasets, which are part of this release.

    iii. Quality and methodology information

    The RSI Quality and Methodology Information report details the intended uses of the statistics in this bulletin, their general quality and the methods used to produce them.

    iv. Revisions triangles

    Revisions to data provide one indication of the reliability of main indicators. Table 8 shows summary information on the size and direction of the revisions made to the volume data covering a 5 year period. Note that changes in definition and classification mean that the revisions analysis is not conceptually the same over time.

    The data section of this bulletin provides these estimates and the calculations behind the averages in the table.

  5. Relevant links

    A subset of the retail sales dataset will be published on our explorable datasets page. Please note the link will not work until the data are published.

    Retail sales in 2015

    Disclosure control policy

    Comparability of RSI Sales and External Indicators

    RSI Workplan

    RSI Quality and Methodology Information report

    Revisions to the Retail Sales Index

    BRC Sales Monitor April 2016

    International Measures of Retail Sales

    National Accounts Workplan

    Why is the retail sales revisions policy different from the National Accounts revisions policy?

    Impact of quarterly employment question on the monthly survey response

    Investigating the effect of quarterly collection of employee jobs data on the estimated standard error of change for total turnover on the Monthly Business Survey

    Government Statistical Service (GSS) uncertainty guidance

  6. Publication policy

    Details of the policy governing the release of new data are available from the UK Statistics Authority website.

  7. Accessing data

    The complete run of data in the tables of this statistical bulletin is available to view and download in electronic format using our Time Series Data service. Users can download the complete bulletin in a choice of zipped formats, or view and download their own sections of individual series.

Back to table of contents

Contact details for this Statistical bulletin

Melanie Richard
Telephone: +44 (0)1633 455602