Quality data analytics start with survey design. Geo Strategy Partners leverages a tool box of quantitative methodologies and data analytics techniques to provide actionable insights to clients. Utilized appropriately and delivered with strategic analysis resulting in recommended tactics and strategic recommendations, the right data analytics can illuminate the path to market with surprising precision.
Purchase decisions are made against a bundle of values. Knowing which value-driving attributes are most important is critical to crafting a value proposition, determining the path to market, or developing strategic messaging. We like to determine both stated and unarticulated importance and utilize different analytical techniques such as those that measure actual behavior instead of stated behavior to elicit them.
Meeting unmet needs can provide the keys to the kingdom when it comes to entering a new market, usurping an entrenched competitor, or developing new products. At Geo Strategy Partners, we employ analytics that measure the delta between importance and satisfaction on outcomes not features. When combined with other techniques, unmet needs analysis can produce game-changing insights.
When you really need to know what is most important, Max-Diff can be the ideal tool. Sometimes standard ratings of attributes on a 1-5 or 1-7 scale do not provide enough clear contrast. Max-Diff methodology forces a respondent to make a continuous set of trade-offs until the rank order of importance is clear.
Sometimes decision-making is complicated and it can be challenging to determine the right combination of product, price, and service features that are most compelling. Conjoint (and discrete choice) analysis measures preferences for product features, shows how changes in price affect demand, and forecasts likely acceptance of a product if brought to market. In making respondents trade-off between different bundles of offerings, conjoint reveals expected buying behavior.
Perceptual mapping is a useful technique to display the relative importance/association/perception of attributes in a visual manner. It also is a useful way to compare performance or perception to competitors on a feature-by-feature basis.
When you need a head-to-head comparison of your firm’s performance against that of your competitors across a series of attributes, use of brand battleground analytics can be useful. This technique is most useful when you have a large sample of customers who have experience purchasing from multiple suppliers. This tool allows clients to address areas of competitive weakness and exploit areas of competitive advantage.
Geo Strategy Partners employs a variety of segmentation tools to allow clients to focus sales and marketing campaigns toward customers that are likely to be early adopters of new solutions or in the “sweet spot“ of good fit for a proposed value proposition. Segmenting allows clients to tailor campaigns to different strata of end-users according to buying behavior or profile.
The chosen method of segmentation should be flexible and adapted to the situation based on two key elements: 1) how the customers actually cluster in the market place; and 2) how those clusters can best be categorized and targeted.
Ultimately, the business goal determines the type of data that will be used for segmentation and the variables that will be used to support business decisions.
- Dependant variables
- Based on the business goal, we need to determine what we are trying to predict
- Segmentation variables
- Based on what we are trying to predict, we determine what type of segmentation is most appropriate and then determine the predictive variables
- Profiling variables
- The predictive variables must relate to an easily identifiable profiling variable. For example, a certain attitude or the way people like to learn may predict the desired behavior but be difficult to identify; correlations with profiling variables must be established to support targeting.
Most market opportunity studies include an element of market sizing. Market sizing for industrial and B2B markets is not simple. We typically combine primary and secondary data to build market sizing models- often employing both a bottom up and top down approach. Models can contain myriad variables: new construction versus expansion, cost of acquisition versus lifecycle cost, length of life/rate of replacement, competitive solutions, preferred brands, decision cycle, regulatory landscape influencers, etc. Typically, we break market sizing analysis down to addressable, viable, and winnable market opportunities.
We also complete sensitivity studies to test business and production plans.
Net promoter score
A standard customer satisfaction measurement is the net promoter score. Respondents are asked if they would recommend a supplier to their peers. The advocates minus the detractors = the NET PROMOTERS.
A meaningful customer satisfaction tool is the secure customer. The intersection of overall satisfaction, likelihood to recommend, and likely to repurchase (loyalty) represents the subset of “secure customers.” Having this visibility allows you to segment this highly valuable customer group.