More of the Same, Only Different

How B2B organisations can leverage social data

B2B and B2C. Totally different customer types. Totally different business models. Totally different marketing and sales strategies.  
Based on this, you might think that there is very little overlap between what works for B2C companies and what works for B2B companies. In many ways you’d be right, but there is at least one resource that can work equally well for both: social media data.
In the last few years, the field of social media analytics has grown rapidly, but the belief that it is only useful for B2C enterprises has remained persistent. But it’s also wrong. In this post, we will talk about some of the ways B2B companies can use social media data to answer some of their most pressing business questions.
B2B companies still operate in the same world: the world in which all those totally different customers are people. And all of those people have opinions. And many of them will voice those opinions online, on forums, blogs, and social media…
It makes sense, then, that trying to understand those customer opinions and motivations by monitoring online chatter can be equally valuable for a B2B organisation as their B2C counterparts.
So how can B2B companies leverage social data to better understand their customers and make smarter decisions about their product, marketing and sales?
Here are three points to consider:

Scaling down is not a problem.

The B2B conversation may be smaller than the B2C one, but the capabilities of a good listening and insights solution stay the same. Users can still get all the insights and analysis from a good platform as for any ‘larger’ search. If anything, the smaller scale of searches may make it easier for B2B companies to quickly separate the signal from the noise and surface relevant insights.
Moreover, a relatively ‘small’ conversation from social media is orders of magnitude larger than the customer data B2B companies are used to. The limitations of scale in traditional market research (the focus group of 10 people, the survey sent to 101 respondents, etc.) never stopped those methodologies from being key tools for B2B organisations, so why would we reject looking at a few thousand opinions just because it’s not a few million?
One reason for a relatively ‘small’ conversation may be that the topic is highly specific, and technical. One example of this is the concept of ‘Precision Medicine’. While there is an online conversation about the subject, sudden interest and coverage mounted thanks to a political announcement of investment by the US government. While this was interesting, it is likely not useful to healthcare firms interested in understanding what customers (hospitals, healthcare providers) want from Precision Medicine technology and hardware. Using machine learning technology to categorise the conversation, the valuable ‘industry conversation’ can be quantified, analysed for trends and themes, and even isolated for potential lead generation.

Look ‘out of the window’ for context.

Any analysis platform that offers truly unlimited historical data allows organisations of any type to look far and wide, beyond their own business, brand, and products. For B2B organisations, this is an important function — when there may not be huge amounts of conversation, or that which is out there is fairly technical or ‘trade-insider’ driven, the ability to look at the context in which you operate can offer real value.
By all means start by looking ‘in the mirror’ at your own brand, products, and activities, but remember to then look ‘out of the window’ for industry context.

Consider specific research questions.

Rather than sticking to the usual ‘brand monitoring’ metrics beloved by many B2C organisations and high profile campaigns, where volume and basic sentiment measures rub shoulders with the occasional word cloud, businesses should take the chance to go deeper. By viewing social media data as a source of unsolicited opinions, B2B companies can take a market research view and start trying to answer specific questions driven from business objectives.
So, rather than ‘how many mentions did my server-hosting business get on Twitter last month?’, focus instead on ‘what are the factors that drive SME decision-making when selecting a data-hosting partner?’, for example.
One example here is how food manufacturers — many of whom do not sell or market their products to end-consumers, but to supermarkets, restaurants, and stores — may still wish to get a deep understanding of what end-consumers are doing, and what they want, as the trends in demand will soon track up the supply chain back to the manufacturers. For example, a company making sauces and marinades for meat may be very interested in commissioning market research, and/or listening to online social conversations, about the drivers and trends of barbecuing and grilling.

There’s plenty more specific use cases for B2B organisations that could be listed here, from user-generated-content inspiration to sales lead generation, channel / supplier assessment to augmenting the annual report. And if all of this still isn’t enough reason for a B2B organisation to consider such a data-driven approach, some social listening platforms also allow clients to upload data from other sources, such as call centre records or traditional market-research surveys, for analysis alongside public online data to gain a broader understanding of the true voice of the consumer.
To summarise, social data has a role to play in many scenarios.  The insights it can generate can inspire and inform action across the business, whether that business be B2C or B2B.

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