The document summarizes the results of a survey measuring the impact of COVID-19 on the reputation of various industries in Canada. The key findings are: - Nursing/long-term care homes, retirement homes, and meat packing facilities are suffering clear reputational damage from their response to COVID-19. - Grocery stores, hospitals, and pharmacies received the strongest positive ratings for their response and are building their reputation. Restaurants also received high marks. - While most industries saw improved perceptions from April to May 2020, construction, banks, internet service providers, and electricity utilities saw statistically significant improvements in their reputation impact scores.

1. STRICTLY PRIVILEGED AND CONFIDENTIAL
May 2020
Release Date: May 21, 2020
Field Dates: May 15, 2020 to May 20, 2020
COVID-19 and Industry Reputation

2. COVID-19 is having dramatic effects on our society and our economy. We won’t know the full long-term implications of this outbreak for
months to come.
In our latest wave of COVID-19 surveys, we once again measure the impact the outbreak is having on the reputation of several key
industries in Canada. This wave report includes tracking from April for 14 industries as well as data for 12 new industries that we did not
test in April.
The study finds that 3 industries (Long-term care homes, retirement homes, and packing facilities for meat) are suffering clear reputational
damage as a result of COVID-19. The strongest performing industries remain the same: foremost are hospitals, pharmacies, and grocery
stores. The restaurant industry also receives high marks.
Understanding the Impact of COVID-19 on industry reputation
May 21, 2020

3. Destroying Reputation Building Reputation
Reputation at Risk
Reputation Building
Opportunity
Reputation Impact
More negative Mixed positive and negative More positive
Engagement
Very
High
Very
Low
Measuring Reputational Impact
When we measure the public’s perception of industry response to the COVID-19 outbreak, we find that for some industries more people have an opinion – whether
positive or negative – than other industries. We call this engagement. When we compare this to the reputation impact we see the potential for industries to build
reputation or put their reputation at risk.
Perception of COVID-19 response more poor than good
50% or more of respondents say either good or poor
Perception of COVID-19 response more good than poor
50% or more of respondents say either good or poor
Perception of COVID-19 response more good than poor
Less than 50% of respondents say either good or poor
Perception of COVID-19 response more poor than good
Less than 50% of respondents say either good or poor

4. Destroying Reputation Building Reputation
Reputation at Risk Reputation Building Opportunity
Reputational impacts: Grocery stores, hospitals and restaurants are
building on a positive reputation with their response to COVID-19
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
-100% -80% -60% -40% -20% 0% +20% +40% +60% +80% +100%
Three of the industries tested are seeing clear negative impacts with high engagement and net negative impact scores from Canadians. On the other hand grocery
stores, hospitals, pharmacies, and to a lesser extent restaurants are seeing high engagement with very positive reputation impacts.
Engagement
Very
High
Very
Low
Reputation Impact
Suffering reputation damage:
- Nursing/long-term care homes
- Retirement homes
- Meat packaging plants
Vulnerable to reputation damage:
- Airlines
- Insurance
- Residential landlords
Strongest positive impacts:
- Grocery stores
- Hospitals
- Pharmacies
Moderate positive impacts:
17 other industries tested showed a
range of more modest positive
impacts with solid engagement.
Restaurants: Stand out from other
industries in this cluster.
More negative Mixed positive and negative More positiveve

5. 5
Detailed Results: Nearly half say grocery stores and hospitals have
had a very good response to the challenges of the COVID-19 crisis
Based on what you have read, seen, or heard, would you say each of the sectors below has done a good job or a poor job of responding to
the challenges of the COVID-19 crisis?
[asked of all respondents, Total n=1,500; split sample each industry is asked of half of the sample at random]
Q
45%
39%
48%
26%
27%
23%
23%
19%
27%
18%
19%
15%
19%
36%
35%
27%
35%
29%
32%
30%
34%
28%
31%
31%
32%
27%
10%
13%
10%
21%
18%
22%
20%
23%
20%
23%
21%
25%
18%
4%
4%
4%
5%
5%
5%
6%
5%
8%
7%
7%
5%
5%
1%
1%
3%
3%
2%
3%
1%
2%
4%
2%
3%
3%
1%
4%
8%
8%
9%
19%
15%
19%
16%
12%
19%
19%
19%
31%
Grocery stores
Pharmacies
Hospitals
Restaurants
Commercial transport
Electricity utilities
Streaming service providers
Independent retailers
Internet service providers
Big box stores
Universities
Nurseries and gardening stores
Farms and ranches
Very good Somewhat good Neither good nor poor Somewhat poor Very poor Don't know
Net Good
+75%
+69%
+68%
+53%
+49%
+47%
+45%
+45%
+43%
+40%
+40%
+40%
+39%
Strongest
Positive
Impacts
ModeratePositiveImpacts

6. 6
Detailed Results: Half say nursing/long-term care homes have had a
poor response to the challenges of the COVID-19 crisis
Based on what you have read, seen, or heard, would you say each of the sectors below has done a good job or a poor job of responding to
the challenges of the COVID-19 crisis?
[asked of all respondents, Total n=1,500; split sample each industry is asked of half of the sample at random]
Q
18%
22%
17%
14%
14%
16%
17%
9%
6%
10%
9%
10%
11%
33%
28%
29%
30%
31%
29%
24%
25%
21%
18%
20%
18%
16%
23%
22%
23%
23%
24%
24%
24%
25%
24%
24%
17%
15%
14%
8%
8%
6%
6%
8%
9%
10%
15%
14%
12%
22%
19%
19%
5%
3%
3%
3%
3%
3%
5%
9%
6%
9%
16%
25%
31%
12%
17%
23%
25%
21%
20%
20%
18%
29%
26%
16%
14%
10%
Banks
K-12 schools
Colleges & CEGEPs
Manufacturing
Construction
Public Transit
Cell/mobile phone service providers
Airlines
Residential landlords
Insurance
Meat packaging plants
Retirement homes*
Nursing or long-term care homes*
Very good Somewhat good Neither good nor poor Somewhat poor Very poor Don't know
Net Good
+39%
+38%
+38%
+35%
+33%
+33%
+26%
+10%
+7%
+6%
-10%
-15%
-23%
*Note: In order to clarify the difference, the fuller descriptions given for retirement and long-term care homes are “Nursing or long-term care homes for seniors in need of active day-
to-day assistance/care” and “Retirement homes for more independent/healthy seniors who need limited/moderate assistance”
Risking
Reputation
Damage
ModeratePositive
Impacts
Suffering
Reputation
Damage

7. 7
-20%
0%
+20%
+40%
+60%
+80%
-20% 0% +20% +40% +60% +80%
Positive change
Negative change
April to May Change: Most industries are performing better now
than in April, 5 have seen a statistically significant positive change
This chart shows tracking from our survey in April 2020 to
these May 2020 results.
The Reputation Impact Score from April (% who say
“Good” minus % who say “Poor”) is shown on the
horizontal axis. The score from May is shown on the
vertical axis.
Industries above the line have seen improvements
between April and May. Industries below have seen
declines in their score. Differences that fall into the grey
band are not statistically significant.
Five industries have seen statistically significant
improvements from April to May. The largest of these
increases are for the Construction industry which
improved from +16% to +33% and Electricity Utilities
which improved from +31% to +47%.
Construction
Banks
Internet Service Providers
Electricity Utilities
Streaming service providers
April: Reputation Impact
May:ReputationImpact

8. Methodology

9. These are the results of an online survey conducted between May 15th
and May 20th, 2020.
Method: This online survey was conducted using INNOVATIVE’s Canada 20/20
national research panel with additional respondents from Lucid, a leading provider
of online sample. Each survey is administered to a series of randomly selected
samples from the panel and weighted to ensure that the overall sample's
composition reflects that of the actual Canadian population according to Census
data to provide results that are intended to approximate a probability sample.
For the industry reputation questions, each industry is asked of half the sample at
random to reduce survey fatigue.
Sample Size: n=2,266 general population, 18 years or older. The results are
weighted to n=1,500 based on Census data from Statistics Canada.
Field Dates: May 15th to May 20th, 2020.
Weighting: Results for Canada are weighted by age, gender, and region to ensure
that the overall sample’s composition reflects that of the actual population
according to Census data; in order to provide results that are intended to
approximate a probability sample. Weighted and unweighted frequencies are
reported in the table.
Margin of Error: This is a representative sample. However, since the online survey
was not a random probability based sample, a margin of error cannot be calculated.
Statements about margins of sampling error or population estimates do not apply
to most online panels.
Survey Methodology
Note: Graphs may not always total 100% due to rounding values rather than any
error in data. Sums are added before rounding numbers.
9
Unweighted
(n)
Unweighted
(%)
Weighted
(n)
Weighted
(%)
Males 18-34 226 10.0% 206 13.8%
Males 35-54 257 11.3% 251 16.7%
Males 55+ 688 30.4% 272 18.1%
Females 18-34 247 10.9% 204 13.6%
Females 35-54 310 13.7% 260 17.4%
Females 55+ 538 23.7% 307 20.4%
BC 431 19.0% 204 13.6%
Alberta 336 14.8% 170 11.3%
Prairies 113 5.0% 100 6.7%
Ontario 880 38.8% 573 38.2%
Quebec 368 16.2% 350 23.3%
Atlantic 138 6.1% 102 6.8%

10. © Copyright 2020 Innovative Research Group Inc.
For more information, please contact:
Greg Lyle
President
(416) 642-6429
glyle@innovativeresearch.ca