Question

1. recognize how some computer-aided methods are used in segmenting.

It needs to be at 3/4 pages related to marketing

Answer 1

Computer aided detection (CAD) is a new technology designed to improve cancer detection on imaging by minimising the chance of human error.

The first application and most commonly used example is the mammography.Mammography is an investigation that is heavily dependent on the examiner - it's a (trained and experienced) human being looking at a (x-ray) photo of a breast.

It should look something like this: strands of fibrous tissue (white) somewhat evenly distributed across the fatty tissue (grey).Now, computers haven't traditionally been able to compete with the human brain in pattern recognition, but as we all know, computers are getting better every year. We've now reached the point where they are starting to offer valuable information in select investigations, such as mammograms. Likely their role will increase in the following decades.

What are marketing segmentation strategies?

What are the best CRMs for small businesses in 2020?

Segmentation is the process of dividing up the market (i.e., all consumers) or a company’s customer base into distinct subsets, where any subset could conceivably be selected as a marketing target to be reached with a distinct marketing mix. Segmentation enables target selection, profiling, and the development of distinct marketing strategies tailored to meet the needs of heterogeneous target audiences.

So: your question could be interpreted at least a couple different ways:

1) How can segmentation be applied to marketing strategies?

2) What are strategies (really: methods or techniques) to develop a market segmentation?

I’ll try to address both below...

1) How can segmentation be applied to marketing strategies?

Segmentation identifies the target audiences most likely to deliver the highest return, allowing marketers to better-manage their marketing investments. It also enables marketers to derive insights applicable throughout the customer life cycle—improving the effectiveness of both acquisition and retention strategies.

By leveraging segmentation insights, marketers can develop data-driven acquisition strategies—more likely to increase conversion and revenue. This includes channel planning, pricing strategies, targeting, message optimization, and media mix modeling.

Segmentation-informed customer retention strategies allow marketers to communicate relevant messaging and create a more positive customer experience to minimize churn, generate growth, and encourage referrals. Segmentation insights inform customer retention tactics including message optimization, cross-sell/up-sell, and product/service bundling.

2) What are strategies (really: methods or techniques) to develop a market segmentation?

Before launching a segmentation project, take some time to identify your specific needs and outline all of your intended use cases—especially how your segmentation insights will be used to impact business goals. This will help inform what data and which techniques will be best suited to your needs. Generally, you should strive to incorporate multiple types of data in your segmentation, and leverage multiple segmentation techniques in order to capitalize on the unique benefits—and mitigate the individual weaknesses—of each.

You should leverage your own, internal data, first. Then, different types of data may be incorporated to develop a 360-degree view of your distinct customer segments. This could include:

- Demographic data: variables such as age, gender, income, occupation, nationality, family size, etc.

- Geographic data: customer household location and related descriptive variables, such as cost of living or urbanicity

- Attitudinal data: reasons why customers use products and services.

- Behavioral data: actual purchase behavior, transactional data, and customer interactions.

- Preference-based data: variables such as media, channel, and product preferences.

- Psychographic data: customer beliefs, opinions, habits and lifestyles.

- Customer state data: the status of the customer’s relationship with the business (new customer, lapsed user, etc.).

- Needs-based data: perceived drivers and trade-offs in purchase behavior.

- Value-based data: customer revenue, profit, and lifetime value.

Segmentations may be built using various methods or techniques—each with unique benefits and limitations. These include:

- Data-driven/statistical techniques—which are effective for direct-response marketing, since coding business rules derived from purely data-driven segmentation methods is relatively straightforward. However, purely data-driven approaches often fail to provide meaning to the segments and lack context; they do not answer “the why”, and thus don’t necessarily result in smarter marketing strategies.

- Research-driven approaches—or survey-based methods using self-reported information. These are useful for building branding and communication roadmaps, but are difficult to map to your CRM data.

- Experience-driven methods—which incorporate attitudinal and psychographic. The resulting insights can be helpful for building customer personas and useful in website design strategy and optimization, but are difficult to apply to outbound targeting.

- Online cookie-based audiences—which are primarily useful for online targeting.

But keep in mind that acquiring, integrating, and analyzing the data is just the beginning. Next comes the “art” of segmentation—e.g., turning your insights into descriptive personas applicable to your specific use cases. Finally, you’ll want to measure the effectiveness of your segmentation by tracking performance in terms of your segments.