Jefferies, the international investment bank initiated coverage of clothing retailer ASOS last week with a buy recommendation.
According to equity researcher David Reynolds, the buy recommendation is in part based on the fact that ASOS increased its Share-of-Influence (SoI) of the online debate, when compared to benchmark companies Zara and H&M (SoI is one of many core metrics and indices produced by Onalytica that when trended traditionally acts as a leading indicator for market share, brand reputation and other corporate objectives).
Reynolds said “Their share of influence is growing, more so among the key influencers; in fashion, that's gold dust.”
The thorough (47 page) analysis which leads to the buy recommendation showcases the use of Onalytica InfluenceMonitor and provides a good overview of our methodology; we even got our logo on the front page!
The buy recommendation was initiated at a price of 1850.58 pence on the 7th of September with a price target on 2199 pence. Today, Sep 19th, the stock closed at 2076.88 after trading as high as 2250.18.
Pictures below show the front cover (cobranded Jefferies + Onalytica) and a page with some of the analyses from Onalytica InfluenceMonitor.
Following on from my previous post about who are influential in the debate on Big Data I decided to have a look at how much attention some of the main players are drawing and how it has developed over time. Our market intelligence platform, InfluenceMonitor, has the answer (and keeps it up-to-date).
The chart below shows the Share-of-Influence (SoI) of 9 brands often associated with the Big Data debate.
SoI is the share of the mention, but with each mention weighed in with the measured influence (on the topic of Big Data) of the voice that makes the mention. The direction of SoI is often a leading indicator for the direction of market share.
The graph shows a number of interesting trends.
First, notice how Oracle has really done well in Q4 and Q1 (so far).
Second, HP seems to be losing out. The Autonomy deal announced in Q3 11 did seem to buck the negative trend in that quarter, but hasn’t helped in Q4 and Q1 12.
Third, McKinsey, a thought leader in the space, have grown their influence almost 9 fold from Q1 11 to Q1 12.
Looking at the graph the big question is clearly, “what did Oracle do that so dramatically moved the needle?”
Well, big data (sorry) helps answer the question.
Using the root-cause analysis function in InfluenceMonitor it turns out that the increase in Oracle’s SoI from Q3 to Q4 was driven by several factors. Oracle’s launch of their NoSQL database had a substantial impact and so did the fact that Day 2 of Oracle OpenWorld focused on Big Data and Analytics.
The attention to Oracle in Q1 12 was largely driven by its launch of Big Data Appliance and its partnership with Cloudera.
The screenshot below shows the Root-Cause Analysis in InfluenceMonitor. The box on the left shows what was driving growth from the first selected metric or period to the next. The right box shows what was pulling the metric the other way. So very quickly you get a good understanding of what was moving the needle.
Companies mentioned: Cloudera, HP, Mckinsey, SAS, Teradata, Microsoft, EMC, IBM, Oracle
My colleague Tom Flaye recently introduced me to the Recession index, an index developed by The Economist that tracks the mentions of the word ‘Recession’ in New York Times and Washington post.
It inspired me to take a look at the UK economy in InfluenceMonitor and it came up with an interesting graph.
The graph below shows the share of online articles and blog posts (not just the newspapers used in the original R-index) that mention the word ‘recession’ when they also mention the UK economy.
The blue line is where all articles and blog posts are weighted equal and the red line is where they are adjusted for their measured influence in the debate on the UK economy.
The green line (Gap) shows the percentage difference between the 2 lines.
Although the direction of both the blue and the red line would (according to the R-Index) indicate that the UK Economy is not on its way to a recession the sharp increase of the gap (green line) indicates that those with more influence in the debate on the UK economy have substantially increased their mentions of the R-word compared with other (and less influential) commentators.
Having a great brand is something most businesses aspire to. A business or product with a better brand can command a higher price for comparable products. Organisations spend a lot of resources trying to shape their overall brand, products and services. The stakes are very high because of the sheer size of the investments necessary to develop the right brand.
To improve their ability to manage their brand initiatives and thereby secure a greater ROI on these initiatives, most organisations conduct surveys to understand how customers feel about their brands. These surveys are often conducted every six-12 months. However, in today’s fast moving world this is clearly too infrequent to support an increasing number of tactical decisions.
Being able to quickly understand the effects of an organisation’s marketing communications (and those of their competitors) is essential. By having a constant feedback loop from the market place marketers can constantly understand which initiatives they might want to amplify and which they might want to adjust or scale back.
At Onalytica we are putting enterprise listening and analytics solutions in place for an increasing number of organisations. Several of these solutions include the ability to constantly measure the brand profile of the organisations as well as understand what is driving the brand in the right direction.
One of the models we use to analyse brands describes the brand in relation to a number of different personality traits. These traits are defined as “pillars”.
These pillars form part of “The Davies Model”, which can be found in the great book on corporate reputation; “Corporate Reputation and Competitiveness” by Professor G. Davies et al. (Rudledge, 2003).
The pillars of the standard Davies model are shown below:
Naturally, the pillars and the traits can vary according to the brand and our solution allows full flexibility on how many pillars can be used and the descriptive words that go into each pillar.
I had a look at some brands and how they are discussed in the context of mobile phones, below, is what the brand profiles look like.
First up is Blackberry. For this example, the original pillars taken from the Davies model, shown above, have been used. Notice how the brand changed slightly from Q1 to Q2 of 2011: Chic, Enterprise and Informality were down – Machismo was up:
Then I took Motorola. Motorola’s brand also changed during the first half of 2011:
Enterprise and Chic were also down, but Machismo and Competence in particular were up.
The general model of using pillars and traits can be configured to compare brands according to the dimensions that are deemed important to those brands.
The next graph shows how three mobile phones compare on a number of features such as camera, design and security:
Notice the substantial differences between the three phones that largely target the same consumer segment. Also notice how the Motorola Pro scores so much higher than its competitors on “security”. The Motorola Pro has extra strong encryption and a number of new security features that mean the phone can be controlled and wiped clean, should the need arise. These are features that Blackberry used to be more associated with, but the current positive differentiators for Blackberry Bold 9900 seem to be apps/applications and design.
Battery life and camera are key differentiators for the Nokia E6. Talk time for this particular model is said to be 14.8 hours, with 31 days standby. The phone has an 8-megapixel camera with full-focus and support for HD video recording.
It is clear to see how maintaining an up-to-date understanding of a brand’s profile can help in the management of that profile. Combining this with our solution’s ability to interactively run root-cause-analysis on changes, marketers can quickly see what is driving their brands in the direction they want and thus which of their marcomms initiatives they might consider increasing.
We are happy to announce the new release of InfluenceMonitor. This new release has a number of exciting new features including:
- Corporate reputation management ability - the creation of pillars based on corporate personality types, including targets for benchmarking and evaluation.
- The facility to test new searches before committing them as a live search in the system. This provides more flexibility and aids testing of different search strings in order to achieve a more effective search, quicker.
- The ability to filter analyses by predefined search terms, facilitating multiple analysis permutations.
- The capacity to infill incomplete data views on selected analyses, using the average of the data points already included in the analysis.
- Dashboard tab management with menu and tab grouping to rationalise multiple dashboard scenarios.
- Notifications at dashboard, analysis and insight level so you know where and when to look for new comments and insight from the analysts.
- Improvements to the speed of analysis drilldowns.
If you would like further information on any of these new features please email me – Sophie.hill@onalytica.com.