Little Data: When B2B marketers don’t have access to big data
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Little Data: When B2B marketers don’t have access to big data
While B2B marketers wait for their organizations to adopt big data tools, they can leverage a range of cost-effective data sources to inform decisions that move their companies forward.
The following are some of low-cost or free data sources (little data) B2B marketers, product managers and strategists can use to evaluate market opportunities, competitors, customer needs and overall market trends.
- US Census
- Publicly available reports/articles
- Mining internal data
- Interviewing sales reps and account managers
- Deeper read of customer survey data
- Social media and job sites
- Conducting win/loss interviews
- Reference class comparisons
Hoovers/D&B (or other list sources)
Hoovers (www.hoovers.com) self-service, prospect, list-building tools can help determine the number of businesses in a segment. Once you set your parameters (e.g. Hospitals with at least 500 employees) Hoovers provides counts for the number of businesses in that segment overall and in sub-segments (e.g. hospitals with 500-1000 employees). You can refine your search, start over, etc. to get more data. You don’t pay unless you purchase a list.
US Census Bureau
The Census provides similar data to Hoovers, but has the advantage of historical data which allows you to see if a segment is growing/shrinking (www.census.gov/econ/). One downside is that the Census’ search tools are clunky.
Publicly available reports/articles (desk research)
B2B marketers need to understand the segments they serve, or plan to enter. Insights into market trends, product use, and market dynamics can be gleaned by reviewing publicly-available reports and articles. Government agencies and trade associations produce reports on broad economic trends and share data from market surveys they conduct. Each industry also has its own trade publications that discusses overall trends and challenges.
Analyst reports profile specific markets and product categories. Most analyst reports charge for full access, but there are often nuggets of information in the free synopsis. In addition, the data source is often cited in other publicly-available sources such articles and vendor marketing materials (e.g. we are in the Magic Quadrant).
Many B2B companies issue press releases when they acquire a new customer, make an acquisition, form a partnership, etc. providing insights into the direction the competitor is headed.
Having a reference librarian or researcher can make the information gathering from these sources much more effective and efficient – simply Google searches can waste a lot of time on a goose chase.
Mining internal data
Sometimes, B2B marketers don’t know what data they available because it is spread out across the organization in different systems and databases. Conducting an information audit will identify the data available for analysis. Taking it a step further, combining the disparate data into one database or spreadsheet can provide surprising insights through simple cross-tabs or pivot tables. If you have more advanced analysis/reporting tools, all the better. Some companies have staff and tools that make pulling the data together easy. In others, B2B marketers must slog through the merging, cutting and pasting data and data files.
Interviewing sales & account reps
Sales and account reps have more direct contact with customers and prospects than anyone else in your company. You can use informal one-on-one conversations, structured round-table discussions or simple online survey tools to explore the requests they receive from customers, competitors they see in the market, solutions in place, etc. Their feedback may be biased towards short-term sales, but it can still provide insights into overall market trends.
Deeper read of customer survey data
VOC and NPS surveys provide a great deal of data beyond the overall score – which often gets the attention. For example, reading through the full set of open-ended comments provides context and texture around customer needs. Combining other customer data with NPS data allows you to look at trends and differences across different type of customers (e.g. product segment, sales volume, tenure as a customer, etc.). Manually creating a spreadsheet that combines the data is cumbersome, but often faster than trying to get things combined in your ERP or CRM system.
Social media, and job sites
LinkedIn, Salesforce’s data.com, and Hoovers provide insights into a competitor’s number of employees and revenue. You can see how many staff are devoted to sales and marketing activities, where sales reps are located, etc. Each source will have a slightly different number for these metrics but by looking at more than one you will triangulate on a usable estimate.
Jobs sites such as Indeed.com and the Hiring section of a competitor’s website can indicate if the company is growing and their focus (e.g. are they hiring more marketing people than would be expected, a certain type of engineer, etc.).
A search of SlideShare can uncover sales and investor presentations and similar materials that show how a competitor is presenting itself to the market.
Conducting win/loss interviews
Conducting interviews with recent wins and losses provides insights into the market’s decision process, vendor evaluation criteria, and how you compare to competitors. Win/loss interviews are best conducted by a third-party partner. If using an external partner isn’t in the budget, the interviews should be conducted by someone not connected to the sales process.
Reference class comparisons
The goals of data-driven decisions are to predict the future and narrow uncertainty. Reference class comparisons—an analytical approach, rather than a data source—can help frame likely future outcomes. The past doesn’t necessarily predict the future, but it’s a good place to start. Future product introductions, acquisitions, entries into new markets, etc. are likely to unfold similar to previous efforts. If you predict that the new effort will be significantly different from the past it forces you to evaluate and identify the data that supports your assumptions.
Tying it together
The secret sauce of big data is that it combines disparate data to form a conclusion based on the relationships that exist. Big data uses algorithms, models, and machine learning to create an outcome that is greater than the sum of its parts. B2B marketers do this daily using little data, basic tools and their experience and judgement – the original big data machine.
Collecting and combining the data sources is time consuming and tedious. It also doesn’t answer all the questions – every decision is based on incomplete data. However, it’s worth the effort: It provides insights that will help B2B marketers evaluate market opportunities, competitors, customer needs and overall market trends.