How myclever used Brandwatch to enhance social engagement around Celebrity Big Brother for Gumtree

1. intro slide
2. *BluefinLabs 2014
3. Maximise the sponsorship opportunity Our Job • 3+ million real time viewers nightly • Ensure Gumtree is part of the show, not ‘butting in’ • Increase engagement and reach from unique content
4. Unpredictable & controversialStakeholders & sign off Extreme timings Add value
5. Minute-by-minute charting
6. • Unique content • Established Gumtree as experts • Increased reach Resulted in:
7. Not only did we monitor sentiment but also used Brandwatch to predict the order that the finalists left the house! We were BANG ON! It enabled us to prepare and create unique content in advance to push out during the live show.
8. Knowing that Calum Best wasn’t likely to win, myclever created bespoke graphics to tweet, to great success! RT’s: 123 Favourites: 345 Replies: 7 Impressions: 481,035 We even got RT’d by the man himself!
9. Threshold and Regular Alerts
10. x20 more website referrals x15 more Gumtree blog visits 32,000,000 organic brand impressions Over 3,000 tweets ‘in the moment’ Share of voice increase Brand mentions doubled +22% positive sentiment change
11. Some of Gumtree’s Best Bits
12. “myclever Agency played a valuable role in bringing our sponsorship of Celebrity Big Brother to life. They came to us with big ideas and executed them brilliantly. They tracked big data across the social web to measure the popularity of the Housemates. But undoubtedly their biggest achievement was watching every minute of the show, and live-tweeting along with thousands of superfans, delivering over 32m organic impressions overall and gaining massive reach for our brand association.” Sam Diamond, Head of Brand, Gumtree
13. 1. Involve Brandwatch as soon as possible 2. Optimise queries 3. Use Datawrapper for speed 4. Share social data to the wider team 5. Promote across all platforms 6. Engage with new audiences
14. Thanks/Questions @mycleveragency #BrandwatchTips

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MCA
MCA>Ruxandra
RUX
In the next couple of slides we’ll be looking at various Brandwatch features that can be used to track live events, specifically focusing on how they were implemented and which were the results in CBB’s use case. We aim to show what worked really well for them, so that hopefully you’ll be able to gain enough knowledge and info that can be applied when monitoring your own events.

To get started, one of the BW features highly recommended when tracking events, is minute-by-minute charting -which helped us uncover which were the top conversation spikes, whilst the final was airing. As shown in the top chart, the online buzz was driven by contestants being voted out and leaving the house, whilst the top spike happened when the CBB winner, Katie Price, was announced.

We were able to have a look at what the top 3 spikes meant really quickly. When clicking on a spike , the app will show you all mentions that were tweeted that particular minute, but as in this case the volume of conversation is pretty high, going through all of them to get a rough idea of what people are talking about can be quite time consuming. So, that’s when the BW topic cloud comes in handy. By going to VIew > Topics we instantly discovered that the biggest spike was driven by the announcement of the winner.

So, what is this useful for you might ask…?

This helped MCA:

get a better understanding of what is driving online conversation during the show
also using this feature, they could easily monitor how trends started and who initiated them
As min by min is a new feature that we’ve recently launched in december last year, I’ll take a minute to talk about it as some of you might not be familiar with it.
Minute-by-minute charting allows users to understand the exact moments causing peaks in conversation or topic&sentiment changes.

One common use case for it is tracking and analysing buzz around specific TV shows or live events.

It is a great opportunity to discover what the audience thinks about the content of a show, actors, storylines and even the ads shown in the breaks.

Some of its direct benefits for marketers can be:
better planning future content by learning the exact moments that generate conversation and why
taking advantage of real-time marketing opportunities
analysing trends, how they grew and when they started
interact with influencers & fans in real time
I like to think of Rules as mini queries used to automatically categorise, tag or classify mentions.

One of the most simple uses of Rules is to track brands, topics and other key terms within your query. For example, in your brand’s query you could set up Rules to automatically categorise mentions in that query that also include particular products, then track them and compare against each other over time.

Once you’ve created a rule, the next step is marking up mentions into categories or tags.

For CBB, we’ve set up rules & categories for each housemate and we were then able to have a look at not only the general volume of conversation around CBB, but at the buzz around each contestant. Furthermore, we were able to extract insights on who’s the most popular/least popular housemate, what’s the sentiment breakdown for each of them and observe which contestant generated most engagement.

On the slide, you can see an example of a rule that we wrote to capture all mentions of Katie Price, as well as the category we created to be able to track, measure and compare conversation on all housemates.
We named the category “Housemates” and then added as a subcategory each contestant. Similarly, to the Katie Price rule, we’ve set up one for each of them. This helped us reveal who are the most popular housemates and perhaps unsurprisingly, the ones who generated most conversation were Katie Price, Katie Hopkins and Calum Best (the last 3 left in the house).
By setting up extremely granular queries MCA were able to dissect chatter to analyse which Housemates were receiving the most mentions each minute.

This is a great example of how our minute-by-minute feature and setting up rules and categories can be used together to reveal interesting insights.

This helped produce original content, established Gumtree as experts in terms of engagement with superfans, it increased their reach on social and lead to more engagement on Twitter. This type of ‘geeky’ content stood us apart from all of the more ‘gossip; related content which meant we had an angle and more success when outreaching.

On opening night we tracked mentions of all the celebrities to look out for spikes to turn into content for both the Gumtree blog and for Twitter outreach.

All-together, mentions of Gumtree (both CBB related and general ones) peaked in January. Compared to December, when they had 6890 mentions, in Jan there were almost 12000 mentions.
As most of you already know, Brandwatch can be used for multiple purposes. Finding leads, tracking competitors, finding influencers, measuring owned vs earned activity, but there’s another use case particularly useful to tracking TV shows or live events. Making predictions!

Having complete flexibility and access to 22 Boolean operators when it comes to creating queries, users can be as specific and as granular as they like.

In the past, we’ve used Brandwatch to predict Oscar Winners and managed to get 15 out of 18 awards correct and showed that social media, with the right guidance, is a credible data source for identifying future outcomes.

To give you an example, this is how we captured all mentions of all Twitter fans saying they’re thinking Katie Price will be the winner.
We also had a look at sentiment and discovered that contestants that triggered the most positive mentions were actually the ones who remained the longest in the house. If we have a look at the last 5 left standing, Michelle with the least positive sentiment was the first one to go, followed by Keith, Calum and Katie Hopkins.
Again, this type of insight helped us massively when it came to creating content…..
Having looked at that data on the night,we had already anticipated that Calum wasn’t going to win, so after they announced his eviction, we were ready to tweet - the result was loads of engagement, retweets and favourites and even a retweet from Calum himself!
Alerts are another Brandwatch feature that can prove extremely useful when tracking events in real time.

In this scenario, there are two types of alerts that could work well.

Firstly, a threshold alert, which allows you to be alerted whenever a query increases in volume above a certain threshold ( which you get to select yourself), so whenever something important/unusual has happened, you’ll be the first one to know.

You’ve also got the option to go for a regular alert and select “as it happens” if you’re looking for real-time data. However, you’ve also got the option to be alerted every hour, daily, or on a weekly basis. For this type of alert, I’d also have a play with the filters, but deciding which ones to apply it definitely depends on your goals.

Do you want to be alerted whenever a tweet gets retweeted more than 5 times? You can select the minimum & maximum number of retweets depending on the “size” of the event. Do you want to be alerted when an influencer with over 5k followers engages with you and be able to reply straightaway? This is the type of alert you need.
Apart from all the key features we’ve just covered, there are a couple of other components that helped MCA measure the online success of CBB.
Simply monitoring the share of voice between all housemates helped them to create original content and add value to online conversations, which resulted in high engagement rates. These insights were also used for interactions with the contestants and boosted interactivity.
just in case people missed them- this is funny 6 second ident - what people were talking about
These were the most popular and garnered their own hashtags

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