Qbase | Due Diligence Analysis | Business Integration | Get the true picture of customer value in acquisitons

Get the true picture of customer value in acquisitons
What is a business really worth? Some of the analysis services developed over the years by Qbase are ideal in helping to establish the true value, real net growth and measurable customer loyalty when buying a business or when developing a multi-brand strategy. Mergers and acquisitions continue to grow year on year, yet failure rates are significant also, predominantly due to poor integration. Qbase can significantly reduce the prospect of failure through robust, structured analysis of your customers and their purchasing behaviour. The problem is widespread... "58% of companies purchased had a lower Total Shareholder Return [TSR] 23 months after the merger announcement than 3 months before" source - AT Kearney	Qbase business integration service We have an extensive and well established programme of analysis and audit to review a potential business acquisition or when considering the impact of different brands in the same marketplace. Our approach is entirely objective as it is solely dependent on the data we audit. Each project is planned in detail with the client, test data is run to assess the methodology, amendments to the audit and analysis are made and then the work is undertaken. On completion the project is then audited internally before being presented to the client.
Qbase were requested to provide consultancy on the integration of a corporate acquisition, (Euroquipment) within Key Industrial. At first glance both Key Industrial and Euroequipment appeared to be very similar companies with overlapping customer bases which would bring into question maintaining both brands with their associated marketing costs... Read more


		Normalised data saves money Qbase normalises global data from multiple sources, ensuring correct alignment & definitions
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	Propensity Modelling is a predictive tool used to highlight customers/prospects who are likely to undertake an action. A historical period is used to "train" the model, where it considers patterns in prospect/customer tendencies and preferences to undertake the same/similar action. The patterns learned by the model are then applied to a given data set which either scores each record with a probability of undertaken the said action, or applies a group banding of "look-a-like" individuals.


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