The feedback cycle in action

Anyone who has heard me rant before, knows a theme is: you need to explore the views of your tribe; uncover the strengths and areas to improve; then drive change by putting the strengths into your marketing and focus business planning with their ideas.

I recently attended the Huntington Estate Music Festival in Mudgee with the music organised by Musica Viva Australia. It was the 3rd time I’ve been and now see myself as part of their tribe.

Last year they had a paper based feedback survey that festival goers were asked to complete before leaving. I was happy! I naturally looked at ways the survey could be improved, but was happy the initiative was taken.

What really made me excited was that at the start of the festival, Tim Stevens (Huntington Estate owner & winemaker) said in the introduction, how they’d listened and changed as a result of the feedback.

They completed the research cycle and I wanted to describe what I saw of the process and how the crowd talked about it.

Firstly, they listened. They asked for feedback. At events there are two times to do this: at the end of the event and after they have gone home.

1. At the event: has higher response as participants are there and engaged. They are giving feedback on a recent experience, still in their memory. The down side is that it doesn’t give a considered response. In the case of training, this is an important consideration. At an event like Huntington this is a great time.
2. After the event: generally gets lower response rates as participants have returned to their normal lives. If you want to know their considered response, such as in training, then it can be better to gain feedback at this time even with lower response rates.

Secondly, they looked at the feedback. They considered ways to improve from the ideas they were given and had information for marketing.

Thirdly, they changed. A range of initiatives to make the festival even better were implemented. I hear from buyers of research or people who do research in-house, that it isn’t value for money. My response is: what did you do when you got the results? And often hear: we didn’t have time or resources to act on them. Of course, you then didn’t find it value for money!

Fourthly, they communicated the changes as a result of the feedback. They kept communicating how they were seeing ways to improve. This is a great event already, with growing audiences. They have raving fans, who talked about being heard.

They said it was great they improved X, now it would be great if they improved it this way. That would make it even better.

They commented that they saw feedback forms for 2009 and would complete them so the organisers would know their views again. This is an important distinction because declining response rates is a problem. The fact they knew they were listened to, encouraged them to participate again.

The full cycle benefits in building the tribe. That makes the event greater. That makes their business greater.

Do you complete the cycle or just ask for the feedback?

The annoying thing about localis(z)ed spelling

Scenario: You have done a survey and you want to get a quick understanding of the words participants used to answer an open response question.

Solution: A perfect way to do this is to make a word cloud – a visual way to understand the frequency of words; where words with a higher frequency are larger, and words with a lower frequency are smaller.

Problem: The English language has two main spelling systems – the British system and the American system. Read more about the differences at Wikipedia.

Implication: The two spelling systems result in a lower overall frequency for essentially the same word, as they are considered 2 words, and therefore a smaller size in a word cloud.

For example, localise and localize are the same word.  If each are used 5 times by participants, the two words would be smaller than if they were combined to have a frequency of 10 using the spelling of your preference.

To show the impact this has on a word cloud, I selected a group of words with different spelling and put them into a spreadsheet. To create a frequency, I used a formula to count the number of characters in the word [In Excel this is LEN(text)].

Word	Frequency	Word	Frequency
aluminium	9	aluminum	8
artefact	8	artifact	8
color	5	colour	6
disc	4	disk	4
flavor	6	flavour	7
honor	5	honour	6
labor	5	labour	6
neighbor	8	neighbour	9
organise	8	organize	8
program	7	programme	9
realise	7	realize	7
recognise	9	recognize	9
rumor	5	rumour	6
speciality	10	specialty	9

Most word cloud software only allows you to paste in a group of words or upload a file of words, before generating the cloud. You can sometimes automatically merge similar words (for example when there is the word, the plural, and end with ‘ing’ they will merge to be one word with the combined frequency). I haven’t found one, other than CloudMaker, that allows you to personally merge similar words, enabling you to handle the problem of British and American English.

Below, the first word cloud is all the words and to the second word cloud is the merged list.

Fewer words makes it easier to understand but also changes the priorities.

All the words

Merged words

Impact: When words with British and American spelling are mixed with words spelt the same in both systems, the first impression views could be inaccurate.

For example, if there was a single spelt word, such as: national, with the frequency of 10 and one of the dual spelt words, such as: localise with the frequency of 7, then also localize with a frequency of 5, merging localise and localize results in a frequency of 12, which is greater than the single spelt word, national, with a frequency of 10.

This could change your thinking about how the question was answered as localise is more frequent than national.

If the question was: What should our regional focus be? Then merging the British and American systems would result in a different first view, than looking at a word cloud without merging – because localise would be greater than national rather than the reverse when not merged.

Social Media Club

I really enjoy #SMCSYD (Social Media Club Sydney) and when I realised that, as I’m in New York, I will miss the next event on building and managing online audiences, I searched for #SMCNYC (Social Media Club New York) to see if I could head there instead.  Last night #SMCNYC had two topics – the FTC Guidelines for bloggers & Google Wave.

Similarities

Yes, you guessed it, they were both about Social Media. The audience was a combination of bloggers, public relations, researchers, communications and consultants.

Differences

• SMCSYD is about 10 times the audience size of SMCNYC. It is rare to say that something in New York isn’t greater in size than in Sydney. Maybe there are just too many options in New York.
• The last two SMCSYDs have been at the Oxford Art Factory with a bar, while SMCNYC was at the offices of PRNewswire, which creates different vibes. With the next SMCSYD at the University of Technology Sydney, University Hall and no alcohol once the event starts maybe those vibes will be similar.
• SMCSYD has become a trending topic on Twitter during the event. Matt Hurst and I were the most prolific twitters during the event. Although I’m a quantitative mind, I haven’t done the math, maybe it is just the difference in audience size, but I think Sydney-siders tweet more at these kinds of events.
• The great thing about SMCNYC is that the smaller group allowed for some great discussion, so that the speakers were more facilitators in a conversation rather than presenters that SMCSYD has.  So depending on your preference – speakers get more air-time in Sydney, there is more debate in New York.
• SMCSYD has a Twitter feed behind the speakers during question time, so that questions are a mix of those coming from the feed and those from the floor.  This means there is a conversation on the floor and a conversation on Twitter – everyone can laugh about a tweet in the feed and the speakers can get a little confused about whether it is something they said. It also means that someone not there can ask a question, or someone at the back can ask questions with the same opportunity to have it answered as someone at the front.
• On the personal side, I walk into SMCSYD knowing people, whereas I walked into SMCNYC without knowing or following anyone there on Twitter. The crowds at both are very friendly and it is easy to meet new people. Sometimes starting cold can be an advantage because you don’t gravitate to those you know.

I generally create a word cloud after SMCSYD using CloudMaker in Tribal Tool-Kit, here is a word cloud created for SMCNYC (as of mid-day the following day).

The benefit of CloudMaker is the editing features. This is what I did:

• The words were imported in the TweetWords section. The Twitter API limits the import to the last 100 tweets. There were 307 terms imported with 772 terms in total. After the editing below there were 289 terms with 695 terms in total.
• Applied a pre-saved stop word list of terms so they don’t appear in the word cloud, but they stay in the data set. The template includes: a; the; and; to; in; on; I; with; My; For; of; Be; Am; As; At; When; It; Your; First; Put; -; All; Are; Is; So; That; An; If; Its; No; &; Any; Do; Go; from; have; here; there; this; what; will; with; about; that; was; want.
• Added to the stop word list new terms relevant to this word cloud as their higher frequencies would make the rest of the cloud very flat: #smcnyc; @smcnyc; smcnyc; @socialmediaclub; #socialmediaclub.
• Deleted the websites imported so that they were no longer in the list and wouldn’t show in the word cloud. This is easy to do by sorting the list alphabetically. This removed 9 terms.
• Also deleted: 11/16
• I merged similar terms and ones with typos:
  • “1994-5″ and “94-5″
  • “blogger”, “bloggers” and “ftc/bloggers”
  • “blog” and “blogs”
  • “giveaway” and “giveaways”
  • “wave” and “waves”
  • “tonight” and “tonght”
• Gravity and Summit were separate terms with a frequency of 12 so I edited “gravity” to be “gravity summit” and then deleted “summit” so that they became one term together.
• Google had a frequency of 33 and Wave 44. These were edited so it was Google Wave 33 and Wave 11.
• Selected a pre-saved template so the word cloud only had terms with a frequency of 3+, there were 4 terms per row, and Tribe Research colours.

The great aspect to chapters of an international organisation is that they have a common goal or theme, but have their own localised flavour. It was great to be able to attend an SMC in both NYC and Sydney.