The world is fast changing and with the use of technology, property owners are now able to determine the amount of rent a tenant should pay, judging by the human flow to his or her premises.

The new method currently being used in some of the shopping malls like the Sarit Centre enables property owners to know which floors and corners of the building are frequented by customers and the human flow at any of the establishments at the mall.

Other than helping the property owners to gauge the rent each tenant should pay, the technology which captures real time information on human movement in the building, it's also a source of vital information for the tenants.

Such information enables a client gauge whether the floor in which his or her shop is located is the most suitable and whether they should consider moving to a better performing floor.

According to Peter Moll, the Sarit Centre public affairs coordinator, having the system is essential to monitor shopping trends and preferences.

"Managements of shopping centres need to know how many people visit their centre, hourly trends, and just which entrances and aisles within the mall they use," said Mr Moll.

"Traffic flow within the centre can determine prime positions and best unit options and therefore influence the asking (and getting) price per square metre. However, historically we have charged the highest rents for the ground and lower ground floor and the rent for other floors decreases the higher one goes" said Mr Moll.

Mr Moll says the Sarit Centre management became aware of this deficiency while planning for its phase three of automation development whose cost is estimated at Sh1 billion.

They contracted KAPS Ltd an automation company - which had been retained to install the computerised parking fee system at the centre- to come up with a movement counter solution.

Without such counts, he says centre managers are operating blindly and therefore make decisions without the necessary data to support them.

The human counts have also helped to establish the average number of shoppers within the centre at any one time, and likely use of such public facilities as washrooms or potential customers in the food court at lunchtime, for example.

He says that computerised counts are more reliable. He cites that during last year's Christmas shopping season, the centre was receiving an average of 25,000 shoppers daily.

According to Eric Mwandia, the managing director of KAPS limited , the rents of such premises are no longer uniform but determined by the amount of business activity taking place in a particular floor.

The business owners he says, are also able to monitor whether a particular promotion campaign they might have placed either in the building or in other media is working out.

"The people counting system on each exit and entrance helps the malls in space planning, determining the rent of each floor and when the companies need to go for advertisement" said Mr Mwandia.

According to Mr Mwandia, other than the property owners those likely to benefit from the technology are the bill boards advertisers.

With the technology one would be able to know which particular vehicles passed on a particular road and thus be able to make judgment which road exactly to place the advert. This he also says will become handy when deciding the rates of the bill boards.

He says at the moment it is very hard for companies who put their adverts on the bill boards to know which area is a hotspot.

The Sarit Centre instituted periodical and seasonal hand-counts of pedestrian traffic back in 1985 which it claims managed it to record 50,000 plus shoppers on 24th December- Christmas Eve- of that year when there was no competing malls then built. Its first step to move from hand-counts came early last year when KAPS installed the automated system on the Centre's eight entrances and into its exhibition centre.

In retrospect, Mr Moll says the system has been invaluable in establishing vital statistics on customer numbers and the entrances they use to access the centre, and therefore reinforcing data derived, for example, from car park figures.