How We Use Predictive Analytics to Build Better Campaigns
In many organizations, an effective collaboration between marketing and sales teams has led to the use of predictive analytics to establish goals, collect data and drive future planning.
Predictive analytics allow savvy marketers to build more precise and efficient long-term branding and direct marketing campaigns that lead to increased return on investment. However, to maximize the value, you need to understand the best ways to make use of predictive tools.
The following are several of the most impactful ways to incorporate predictable analytics into your strategy for building better campaigns.
Targeting Optimum Sales Leads
As you track data on prospects and customers, your predictive analytics tool is able to pinpoint traits of buyers that your business converts most efficiently. By identifying the highest-converting leads, your marketing team can better invest resources to attract these types of buyers. Not only will you spend more going after the right buyer personas, you can mitigate or eliminate investments in lower-performing market segments.
Conversion rates aren't the only factor to consider in targeting decisions. Some leads require a lot of time and resources with little return. By tracking sales cycle time and other decision process factors, you can weigh these items in your investment decisions as well.
Projecting Lifetime Value
The ability to use forecasting models to project lifetime customer value has great influence on marketing strategies. For instance, companies often make promotional decisions based on predicted LTV within particular market segments or buyer personas.
LTV projections influence decisions on whether to invest in large-scale media campaigns, or to utilize lower-budget digital methods. Decisions on when to execute direct marketing campaigns, mark down prices and remove products altogether also benefit from predictive analytics.
Product and service development is influenced by projected demand within certain market segments. By monitoring data from previous launches, it is easier for marketers to predict potential demand for a newly developed product that is similar.
Research into preferences and features that affect buying decisions is also useful in building demand forecasting models. By creating new solutions that the market wants and launching them at the right time, demand potential is amplified.
As you test responses to promotional messages across channels, you gain data for predicting future responses. Companies can fine-tune social media marketing, for instance, by tracking the channels and message types that drive the desired response.
With predictive analytics, it is easier to craft the right message for the right audience, and then deliver it through the optimum channel.
The best use of marketing resources occurs when you can accurately predict the behaviors or responses of a specific type of buyer.
There are many facets of marketing that are improved through data collection and predictive analytics. Overall, efficient use of resources and return on investment are primary financial considerations. In most cases, predicting accurate outcomes is a far better option than relying on hunches or guesses.
As a firm that specializes in digital advertising, BKV can help you establish predictive analytics goals, collect the right data and build predictive models. See some of our work and then give us a call about partnering with your brand.