Cross selling matrix template

This data mining algorithm works by weighting the occurrence of all possible association rules. Association rules are all possible product combinations. The figure of possible combinations can be a huge number if you have thousands of products. The total number of possible association rules, R, is exponential to the number of items, n, according to the formula below:. In our example, with four products only C, T, S, and M , we will have fifty different association rules. For simplicity, we will not list them all here.

Of course, to implement an apriori with excel, you will have to record them all. Create a column in excel by listing all possible buying combinations. This table will look like the one below. It is essential to note that association does not imply causality. An association amongst products is the measure of co-occurrence and does not represent cause and effect. To learn from your association rules, you need to add support and confidence.

The support denotes the frequency of the rule within your transaction dataset. A high value means that the product combination happens often. The confidence of each rule represents the percentage of transactions containing product C, which also include product M. This calculation represents an estimation of conditioned probability.

Now we need to calculate both support and confidence for each of the association rules. In our example, one could make this for each of the 50 rules or at least for the rules that are present in the transaction database. We will not get into details. N is the total number of transactions, in our example 4. Now, looking at the image above, you can filter by two thresholds: minim support and minimum confidence.

Since we only have four transactions in our example, there is a limited number of options. You will find one rule only satisfying this condition, the rule number S — C. When mining for associations rules with cross-selling algorithms, data scientists usually find three categories of rules: trivial rules, inexplicable rules and actionable rules.

Trivial rules are combinations that are obvious and well-known. For example, if a customer buys a big machine, it might undoubtedly need services. Knowing that the algorithm confirms such a rule usually adds no value. Inexplicable rules are those we cannot explain and add no value either. There is no way to prepare an offer or a cross-selling strategy if the association rules make no sense at all.

This situation often happens in data mining. So, what do you do? Number of Employees Less than 50 , 1,, 2,, 5,, 7,, More than 10, Are you sure you want to cancel your subscriptions?

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Select your country:. Cross-Sell Template Lead Nurturing Conversion Order General marketing email marketing email marketing templates Template CRM Selling new products or services to an existing customer is much easier and far more cost effective! We have mastered the art of building a cross selling solution using QlikView to find the opportunities, generate the cross-selling leads and monitor the results of the cross selling campaign or initiative.

Firstly, we identify the data sources where we anticipate cross selling opportunities to exist. Often the two data sets are not already consolidated anywhere in the organisation. It is therefore imperative to be able to consolidate these sources in a short space of time otherwise the exercise stands the risk of becoming a monster. We quickly establish what the current cross selling ratio is. Today, numerous software tools provide product portfolio roadmaps to manage your portfolio over time.

Many use this kind of overview, along with timelines and other visual aids, to support strategies for a cross-section of products. As with all methods, consider the following when developing or creating a product portfolio strategy or roadmap:. For more resources to help you manage your product portfolio, choose from a variety of free product portfolio management templates. For greater visualization, the BCG matrix is a popular technique that uses an X-Y graph to analyze a product against its overall market.

The Boston Consulting Group developed this premier X-Y grid that measures market growth and market share. Their BCG Matrix depicts four quadrants that distinguish high and low markets and a product's position in those markets.

The products are categorized as s tars, cash cows, dogs , and question marks. Stars , which are dominant products in a growing market, and cash cows , which are legacy products that control a steady or diminishing market, make up the bulk of profitability for a company.

Dogs are low-yielding products in a declining market that drain resources and are contenders for elimination. Product decisions are most difficult around question marks , which are products that have some level of potential for innovation in a growing market. You can enhance investment risk analysis by adding a bubble chart or scoring system to identify breakthrough products versus those that end up in the "dog house".

The BCG matrix helps with long-term product planning. By positioning products in the star, cash cow, dog, and question mark quadrants, you can identify where to invest and discontinue investments.

Some organizations apply their build, hold, harvest, and divest strategies to the BCG matrix. Recommendations for each quadrant are as follows:. In a perfect scenario, products begin their life as question marks, become stars, transition to cash cows, and finally end their life as dogs. Diversification across each quadrant is an ideal and balanced portfolio: stars deliver future growth, cash cows fund the business, and question marks may be the next stars.

The low, medium, and high ratings give a broader view of products to develop, markets to expand into, products to retool, and products to eliminate. A company evaluates each axis as follows:. A product that has high industry attractiveness and high competitive strength should receive maximum investment. A product in a medium or average industry that also has average competitive advantages is a concern.

Finally, a product with low industry attractiveness and low competitive strength is suitable for divestment. The product lifecycle begins with the introduction of a product and ends with its retirement.

Each product that enters the market has a lifecycle — some longer, and some shorter. Analyzing the product lifecycle can help a company determine product strategy, similar to product portfolio management. When a product is first made available, it falls into the question mark or star quadrant of the BCG matrix — somewhere between unknown to high growth and benefit. From the star quadrant, products ideally move into cash cows where the growth is stable, but the benefit is still high.