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Case study: how data convinced management to go social and engage

Social rides roughshod over traditional marketing and sales engagement processes because it has to.

What it lacks in heritage, longevity and familiarity, it gains in a ruthless adherence to mercilessly-objective data.

Put simply, social can be measured, social can be held accountable, and the line between social cause and effect can be drawn with a darker pen and a straighter ruler.

But how do you convince management to consider social for the first time, or as part of an organizational rebuild, or on a programme that has the potential to break moulds but also break hearts?

Once again the answer lies with with data, this time driving results.

Here’s how.

Our client operates at two levels in the marketplace: as a provider of consumer services and as a spearhead technology company operating at the leading edge of R&D.

On both counts it was acutely aware that it had to maintain its market lead. It knew its competition would overtake it in an instant, and it was equally aware of new market entrants attacking it from the side.

Against this fiercely competitive backdrop it wanted to be more active in engaging with influencers to drive the market debate on topics of relevance, in a way that was balanced, constructive, and acceptable to those same influencers.

Who are they?

The challenge was that it had no idea who these individuals might be.

Worse, it didn’t know who from among its employees were already active in the social web.

It didn’t know whether the content it had already published and that it had in reserve was hitting its marketing mark.

It didn’t know anything about levels of engagement with influencers, how that engagement took place, or anything about the effects its current engagement might be having.

It short, at best, it was acting on assumptions.

Making sense, hooked to strategy

The answer was to hook together strategy, technology and management buy-in.


At the core was the client’s objective: identify and engage with those influencers who really counted.

What changed was being able to replace assumptions with data.

The client team members knew some influencers by reputation or as personal contacts. Both groups were ignored – in favour of a list of influencers built on empirical data.

Topics focused on those of interest to the client.

Engagement data identified those influencers of most relevance, but using data that went much further than a static measurement of reach.

True engagement counted most: that complex synthesis of frequency of publication, real-time sharing of influencer content by those reading or viewing it, the numbers of readers and sharers, their networks, and measurements of sentiment.

The analysis needed to be complete and updated in real-time – which can be complex in itself. Influencers don’t update content in sync with each other, or even necessarily to a predictable routine, so there’s no way to know in advance when they will publish.

Which meant real-time monitoring, across multiple social channels, across multiple connections, in some cases across multiple discussions.

The final piece of this dynamic system was the presentation of the information to management: in a real-time dashboard, with the information selected by the company and segmented by influencer, communities, topics, campaigns, share of voice, and other criteria.

Measurable improvements for the business

The impact on the business was immediate.


Engagements shifted to individuals with more influence, on topics about which the company cared.

Content was better targeted, shared more, and on topic.

Employees with connections with influencers were coached internally, and engaged externally.

New connections were made, with purpose, built on insights rather than guesswork.

Executives quickly understood much more about the buying cycles of customers and prospects; priorities were easier to spot and decisions were made on information, not assumptions (or personal preferences).

Insights were delivered daily by choice, but were acquired in real-time – meaning that executives now made decisions essentially on live data delivered to their desktops, rather than acquired painstakingly in arrears.

And the key was the data: evidence that demonstrated that customers and influencers (and employees) were indeed active, that connections could be made and influence exerted in meaningful and authentic ways.



Alan Smith: Alan is Head of Customer Engagement at DIGIVIZER.