Masterclass: Using Brandwatch for Market Research

Editor's Notes

• #5: So to summarise, over the past five years I’ve seen social media research move from being very brand centric, to focusing more on consumers. Social media can provide us an unprompted and self sculpted view of consumer motivations and needs. PAUSE This slide is a bit misleading in that we’ve used the whole space – there should really be a huge blank space to the right to allow for all the future innovations that are still to come. For me one of the most important questions social research is facing now is how to better integrate insights from social media into the existing research mix. We’re starting to map social research more onto existing data held by our clients, but how to make this easier and and more accessible and to use it to gain further insights through data integration is a really exciting challenge facing social research.
• #7: Just data. And it can be wrangled into order like any other data-set. So, panic over, we’re on to step two.
• #19: KEY POINTS For the purpose of this analysis, we’ve broken down “gigs” into three main types; Pop/R&B music, Indie/Rock music and comedy (stand-up). Categorising data in this way can help you to better understand which types of event are most likely to be successful when marketed through social channels, and assist with engagement planning. In the next two slides, we’ll see how you can use categories like this, alongside Brandwatch Demographics data, to better understand who’s talking about/going to your events, and who to target.
• #20: KEY POINTS Here I’m trying to demonstrate the granularity that you can go into. We got this list of acts by searching for those acts who had toured this year, or were going to, or were generally big acts in 2014. We then included them in our search and wrote rules to section them out. Comedians and R&B/Pop both saw a pattern where two or three main artists drove over 50% of the conversation, suggesting the importance of big head line acts to those verticals – social can help you find out who these are and track their popularity over time. Indie/Rock artists saw a more even distribtution, suggesting less clustering/importance on just a few acts, and a need to cater to a wider variety for those interested in this type of music.
• #21: KEY POINTS This map was powered with Brandwatch data, using a third party data visualization tool. It shows how Tweets about gigs were distributed throughout the UK. Mentions were highly clustered in urban areas. Consumers in southern rural/suburban areas were more likely than those in the north to talk about gigs. So long as we have enough data, we can look at how Brandwatch categories break down over geographical regions too, as shown on the next slide
• #22: KEY POINTS This map is showing how conversation about the three most talked about venues was distributed across the UK, indicating how far people were willing to travel for gigs at each arena. The london arenas were far more likely than the Manchester arena to draw people in from further away, even consumers in Scotland and towns nearer to Manchester (such as Birmingham and others in the midlands) were more likely to travel to London arenas than to Manchester. Further analysis could reveal if this was due to particular acts who perhaps were not featured so strongly in northern arenas (in which case this could aid understanding of demand and future planning of events) or it could be that other factors are driving this. For example, people may simply not be aware of the gigs happening in Manchester (in which case increased awareness campaigns could help to draw more people in from the further surrounding areas). It could be that the experience of going to the large London arenas is what the travelling consumers are craving, and a deeper analysis into conversation about these areans could help to inform marketing messaging for the Manchester (and other non-London) arenas, to help them create some similar excitement to that surrounding the London arenas.
• #23: KEY POINTS For this analysis we wrote a search string to bring back people talking about actually purchasing tickets to a gig/event. We noticed a trend in our topic clouds relating to purchase – the appearance of the word “mum” Looking into this further it seemed that a reasonable amount of purchase conversation was relating to parents buying tickets for their kids (especially teenagers). To explore how significant this topic was, we wrote another search string to bring back all that conversation, and found that nearly one fifth of mentions about buying tickets for gigs online relating to parents buying them for their kids. Splitting it down further, in the pie chart you can see that of this conversation, over 80% of it was actually written by the teenager/kid, not the parent. Understanding who it is that is actually talking online, and what their relationship is to the actual purchaser/decision maker can help to inform messaging for social engagement around ticket sales. On the next slide we’ll go into some more details on this…
• #24: KEY POINTS Here we’ve broken down the parent and kid/teen voices by channel – where are each group talking online. Both groups were active mostly on forums and Twitter, however parents were more likely to talk in forums, while their kids were found mostly on Twitter. The kids were also more likely to be blogging. Further research could locate specific parenting forums for targeted engagements and listening. If creating a campaign aimed at the teenagers, Twitter is the highest reach platform, and you could have some success with blogger outreach. To help inform tone and content, you can look deeper into which acts are driving this type of conversation – you can see in the table that almost half was driven by One Direction and the majority was pop/R&B focused.
• #25: KEY POINTS This chart uses the same date range (the last three months) and shows the average day’s activity by the hour. Overall gig conversation starts to pick up at around 8am and builds steadily through the day, accelerating in the evening. This suggests that a large proportion of gig mentions happen in real time, at the events. Again when it comes to buying conversation we see a different pattern, with a sharp peak at 9am, and another later in the afternoon at 4pm, and again at 7pm. The reasons behind these changes can be sought through sampling data taken from each day of the week, and could also be explained and put into context by comparing with other data sources, such as sales figures and the usual timing of sale announcements. This can help to build up a pattern of prompted and unprompted consumer behaviour, and inform planning of times announcements both in and outside of social media. For a full study we’d recommend taking a longer date range in order to come up with some really reliable averages.
• #30: Sample taken from about 7,500 mentions. Accurate to 95% with 5% confidence interval Naturally arising author groups based on manual sampling methodology – highlighting the most vocal/engaged author groups, who are not always the traditional target group. For Pharam the target group is often seen as being the Healthcare Professional, but in terms of social research and engagement, it’s the patients, caregivers and other online authors that can provide the most useful insights. HIV treatment conversation was distinct from other disease areas in that caregiver conversation was very low (only 1% came from a relative/friend of a HIV positive person, previous BW studies showed an average of ~20% caregiver conversation in the UK). The general public (other consumers) spoke almost three times more about HIV treatment than healthcare professionals, suggesting a broad interest in the topic and that online influencers may differ from offline.
• #31: In order to inform messaging around treatment, we need to understand what benefits people are most likely to share/talk about – focusing on these messages could help to boost WOM by tapping into natural interest. In this case, the most highly talked about benefit is the reduction in the likelihood to pass on the HIV virus if the patient adheres to their medication routine. However, we can go one better… and take a look at how these priorities differ among key author groups….
• #32: Here we’ve taken the same benefits and broken them down by author group, revealing quite different priorities Help with targeting different groups Patients – most likely to talk about the impact on their life, allowing them to live normally Other consumers – most likely to talk about limiting the spread/risk of becoming infected. Journalists – focus on the most “newsworthy”/extreme treatments claiming to be potential cures. All author groups – Increased life expectancy resonated across all groups, suggesting a good topic for broader awareness campaigns.