Linus Gregoriadis (Research Director Econsultancy) presentation on some of the findings of the Measure and analytics report for 2015. Presented at the launch of the report at Web Analytics Wednesday July 2015.
2. Background and methodology
• Eighth annual study
• Online survey in April and May 2014
• Nearly 900 respondents, including:
– 57% are client-side marketers and analysts
– 43% are supply-side respondents
• Range of sectors
228 July 2015
4. Two in five organisations don’t use a framework to
structure their measurement requirements
28 July 2015 4
58%
42%
57%
43%
0%
10%
20%
30%
40%
50%
60%
70%
Yes No
Company respondents Agency respondents
5. Two-thirds are lacking a formally documented data
analytics strategy
28 July 2015 5
18% 16%
66%
16%
24%
60%
0%
10%
20%
30%
40%
50%
60%
70%
Yes, with digital as part
of this
Yes, but for digital
analytics only
No
Company respondents Agency respondents
6. Less than a fifth have strategies which straddle the
digital and non-digital worlds
28 July 2015 6
18% 16%
66%
16%
24%
60%
0%
10%
20%
30%
40%
50%
60%
70%
Yes, with digital as part
of this
Yes, but for digital
analytics only
No
Company respondents Agency respondents
11. The vast majority (86%) indicate that their
‘understanding of customers is increasing over time’
28 July 2015 11
31%
55%
9%
5%
1%
Strongly agree Partially agree Neutral
Partially disagree Strongly disagree
12. More than half (55%) ‘use data effectively to build
their understanding of customers’
28 July 2015 12
10%
45%
19%
21%
6%
Strongly agree Partially agree Neutral
Partially disagree Strongly disagree
17. The proportion of companies using a TMS has more than
doubled since 2013: from 24% to 54%
28 July 2015 17
22%
32%
19%
27%
21%
30%
28%
22%
0%
5%
10%
15%
20%
25%
30%
35%
Yes, we / they use a
paid-for solution
Yes, we / they use a
free solution
No, but we / they are
considering this
No
Company respondents Agency respondents
18. But less than half (46%) have mapped out a data layer for
their TMS
28 July 2015 18
46%
42%
13%
37%
40%
23%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Yes No, but we / they want
to do this
No
Company respondents Agency respondents
20. Areas where support from vendors is most in demand
28 July 2015 20
31%
41%
44%
44%
51%
53%
54%
44%
47%
41%
35%
31%
29%
33%
25%
13%
15%
20%
18%
19%
13%
Advising what tools are most appropriate for a
specific task
Recommending the best way of making the
most of a specific tool
Supporting integration with other tools and
technologies from the same vendor
Supporting integration with other tools and
technologies from other vendors
Training end users to make the most of the tool
Translating business requirements into
analytics requirements
Supporting deployment
Critical Important Nice to have
21. Criticality of support or consultancy requirements
versus performance of analytics vendors
28 July 2015 21
75%
80%
81%
82%
85%
87%
87%
35%
48%
52%
51%
57%
55%
59%
Advising what tools are most appropriate for a
specific task
Supporting integration with other tools and
technologies from other vendors
Translating business requirements into analytics
requirements
Training end users to make the most of the tool
Supporting integration with other tools and
technologies from the same vendor
Recommending the best way of making the most
of a specific tool
Supporting deployment
Proportion of companies saying these requirements are 'critical' or 'important'
Proportion of companies rating their analytics vendor as 'excellent' or 'good'
22. At an overall level, companies are significantly more likely
to be happy than unhappy with their vendors
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23. At an overall level, companies are significantly more likely
to be happy than unhappy with their vendors
28 July 2015 23
26. Those who have deployed a big data technology solution are still in
the minority (11%), but a further 24% are considering one
28 July 2015 26
11%
24%
65%
6%
29%
65%
0%
10%
20%
30%
40%
50%
60%
70%
Yes, we / they have
deployed a solution
No, but we / they are
considering this
No
Company respondents Agency respondents
27. Among those that use a big data solution, just under half
(45%) say they use cloud-based technologies
28 July 2015 27
45%
55%
75%
25%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Yes, cloud-based solution No, we / they use our / their own
hardware
Company respondents Agency respondents
28. Just under a third (30%) say they use Hadoop
28 July 2015 28
30% 30%
11%
5%
3% 3% 3%
16%
0%
5%
10%
15%
20%
25%
30%
35%
Hadoop In-house
solution
Google
BigQuery
MongoDB Amazon
Redshift
Cloudera Oracle
ExaData
Other
30. More than half (58%) of companies are using attribution
28 July 2015 30
58%
42%
57%
43%
0%
10%
20%
30%
40%
50%
60%
70%
Yes No
Company respondents Agency respondents
31. But only 8% of those using a model are ‘very confident’
that it is based on facts about their data and business
28 July 2015 31
8%
45%
34%
13%
9%
36%
38%
17%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Very confident Quite confident Unsure Not confident at all
Company respondents Agency respondents
32. Summary
• Companies increasingly using data to build
understanding of customers and then adapt
customer experience accordingly.
28 July 2015 32
33. Summary
• Companies increasingly using data to build
understanding of customers and then adapt
customer experience accordingly.
• Many organisations lacking both a multichannel
data analytics strategy and a measurement
framework.
28 July 2015 33
34. Summary
• Companies increasingly using data to build
understanding of customers and then adapt
customer experience accordingly.
• Many organisations lacking both a multichannel
data analytics strategy and a measurement
framework.
• Respondents positive about vendors though room
for improvement.
28 July 2015 34
35. Thank you
Download the full Econsultancy / Lynchpin
Measurement and Analytics Report
ecly.co/lynchpin-2015
28 July 2015 35
Notas do Editor
Eighth annual report with Lynchpin, formerly the Online Measurement and Strategy Report.
Real bellwether for what’s happening in the Digital Analytics space, we’ve evolved the survey to reflect the fact that web analytics isn’t happening in a silo.
As usual the methodology was an online survey, a very robust international sample, mainly from the UK (about two-thirds)
Some cross-tabs based on company size in the report
A lot of companies don’t have a measurement framework which is worrying. The ‘no’ camp is actually the majority (51%) for smaller companies with a turnover of less than £50m.
Even fewer companies have a formally documented data analytics strategy, 34% in total.
Only 18% have such as strategy which straddles online and offline.
More encouragingly, more companies are looking to grow their in-house analytics teams, with 50% of businesses planning to increase their spending over the next 12 months, up from 46% a year ago.
In contrast, fewer organisations than a year ago say they are planning to increase their technology and consulting budgets.
This year’s research also focuses on the important role for data and analytics in supporting their attempts to build a competitive advantage by becoming more customer-centric.
Data being used for understanding the customer journey, patterns of content engagement … and then used for personalisation and targeting
Currently, two in every five companies (40%) say more than half of their collated analytics data is useful for driving decision-making, an 8% increase since 2014 and the highest proportion since 2012.
Given that companies are fighting a deluge of more and more data, this is pretty positive.
However, there has been a significant drop in the number of respondents who say that analytics ‘definitely’ drive actionable recommendations which make a difference to their organisation. Just 23% of respondents were in this camp, compared to 40% last year, a huge decrease of 42%. This is a stark reminder of the difficulty companies face if they want to make data both insightful and useful.
The 2013 version of this report found that 24% of companies were using tag management systems. Fast forward to 2015 and that number has now more than doubled to 54%.
But less than half of companies (46%) have mapped out a data layer for their tag management system, a process which is a prerequisite for successful tag management and data strategies.
A bit like a look-up table and ‘essentially a dictionary of data definitions in business language’.
A data layer allows you to separate data collection, manipulation and delivery from the web page’s structure.
Supporting deployment, translating business requirements into analytics requirements, and training end users are the three areas where the support of vendors is most in demand. Each of these requirements is rated as ‘critical’ by more than half of responding companies.
Amid all this talk of data, companies need a way to store it and process it. This is where big data solutions come in.
Significantly, more than a third were ‘unsure’ of this, and 13% were not confident at all.