i i'm professor marketing american university change in the night or inference
paul williams i recently categorical probably children's services marketing that builds on some research we
conducted over the last are yours this data flow from the time to try and
we have used for about eleven years prior to getting that in domains
by biased in human a large size firms forty one for and we would want
to studies with these four we present to secure exact in organisations you realise there's
millions of dollars we made by a single by one or two or three percentage
points
and so that focus was their initial focus only in customers the pointing it performs
organisations in two thousand five we will consider your marketing and she solicited articles from
somebody scholars and you'll just real pretty webster don't limit
and others ask them based on your what with the shortcomings what you're the consists
of those articles in that by j was that we in the morning more
may actually work we show a little bit of this morning actions and decisions on
financial performance in for specifically we need to be able to document the financial performance
metrics relating to read from increasing task force that for changes in product or service
delivery
talking back to the financial performance of the four original
so what we came up with it will be the stores to justify was that
what we try to previous years
at that i don't decided using so these longitudinal databases for the research so that
way well as i started analysing the data to see what happens changes over time
that strategies that's the final performance
we focus is that the improvement over most studies are done feel because most a
cross sectional those of eight three hundred by either way time but it doesn't show
that i am i change over time and l s played by the performance
so what or restaurant we went back to looking at something spanish for metrics be
variables look row rescore share a
r y are redraw tested so you try to find estimates
what we try to do it stays databases strategies specifically customer satisfaction representations attractive over
a period of three four five years so that are inside to okay is that
into the changes by four
so that i like to earn representation over all and he saw that some of
the specific financial metrics that we the results came out
okay and you will a particular study we were dealing with a building services industry
when we talk about some heating ventilation and air conditioning systems most exciting research are
want to take relevant and we're dealing with what complex onsets financially as well
there were three main results we found the data that the first one is actually
very strong relationship between customer satisfaction and actual attention with the for the was a
renewal right wherever the satisfaction models
okay but most there is just going to be the case now we got ninety
hours of data group
the second interesting result
was that was for you growth particularly it was a very strong relationship between customer
satisfaction hundred and you wrote cable leading to high level of satisfaction lead to higher
levels of running you wrote with respect to the customer
another interesting statistic we found in our data was customer satisfaction is highly correlated with
small performance is represented by stock price and we also confirm that tokens q six
actually correlation between the model performance for low prices
and what the customers are satisfied
conclusion a i think we show longitudinal data has been extremely insightful interesting and we
have confirmed favourites already
shown in conceptual study we think it is i value to use a more accurate