1. Our task Smart Grid, Smart City Customer Research Findings Arup | Energeia | Frontier Economics | Institute for Sustainable Futures Industry Forum 28 th July 2014

2. Customer Survey

3. 3 3 Survey Background All customers using product for > 1 month contacted Survey via email and phone, in Aug 2013 & Feb-Mar 2014 Surveyed 47% of eligible trial participants Sample sizes SurveyResponses 20131,710 2014 (repeat respondent)994 2014 (new respondent)1,505 TOTAL3,215

4. 4 4 Survey Background Expect some degree of self selection bias in results: Trial participants signed up by choice Respondents to survey may be those more engaged with their product and interested in giving feedback

5. 5 5 Customer Priorities Customers with in-home displays engaged with their energy data much more frequently than those with portals

6. 6 6 Product Interaction Customers with in-home displays engaged with their energy data much more frequently than those with portals

7. 7 7 Actual vs Perceived And increased engagement with feedback data DOES actually correlate with higher energy and peak savings

8. 8 8 Product Interaction But when paired with HAN, Portal can be a powerful tool for bill reductions, despite lower frequency of engagement

9. 9 9 Product Interaction The more energy data was provided to customers, the more they wanted – very few people felt overloaded with information

10. 10 Product Impact Trialled products increased customer energy awareness, control over consumption & ability to reduce bills … but not all customers ‘convert’ awareness to bill reductions

11. 11 Product Impact Tariff & Technology Products Tariff only, Technology only Products

12. 12 Product Impact Changes to routine generally did not involve substantial change to people’s daily routines (left) Self-reported implementation of behaviour change ‘decays’ over time, but not markedly (right)

13. 13 Product Impact Expect lower – but not insubstantial – consumer demand reduction on extreme temperature days Suggests peak prices more effective than rebates for delivering critical peak day reductions

14. 14 Vulnerability Analysis Financially vulnerable HHs were more willing to shift load, more satisfied with their products and felt more empowered to reduce bills

15. 15 Vulnerability Analysis Elderly: older households were less likely to engage frequently with the product, obtain the benefits and derive satisfaction, but having a lower income (e.g. pensioners) offsets some of this ‘age effect’.

16. 16 Vulnerability Analysis Children: Increases the likelihood of the household feeling ‘bill pressure’; limited clear behaviour change difference (slightly higher load shifting); but improved likelihood to recommend.

17. 17 Product Type Analysis Incentivise or inform: Products combining feedback technologies with a tariff/rebate consistently improved customer outcomes across a range of indicators.

18. 18 Product Type Analysis e.g. Ability to reduce bills – average score of +0.2 represents clear trend

19. 19 Product Type Analysis Tariff Type: Peak event products (rebate and tariff) outperformed others across a range of indicators, but BudgetSmart also popular

20. 20 Product Type Analysis Carrot or stick: Rebate customers thought they saved more (below) but tariff customers actually saved more (Frontier)

21. 21 Change Over Time Product Satisfaction: Remained steady or improved for 90% of respondent households.

22. 22 Future Research Dataset available on ICH Multivariate analysis to isolate the influence of specific variables on indicators More cross-question analysis Greater diversity of extreme peak event conditions Choice modelling to interrogate competing priorities (price vs reliability)

23. 23 Questions